{ "cells": [ { "cell_type": "markdown", "id": "a9f65483-6fb1-44f2-819b-bd59faaf5648", "metadata": {}, "source": [ "# Import libraries" ] }, { "cell_type": "code", "execution_count": 1, "id": "af733c31-b05e-4b69-a5a5-cf414d913467", "metadata": {}, "outputs": [], "source": [ "import pandas as pd\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", "import seaborn as sns\n", "\n", "from scipy import stats\n", "import statsmodels.api as sm\n", "from statsmodels.stats.outliers_influence import variance_inflation_factor\n", "\n", "from pathlib import Path\n", "import warnings\n", "\n", "warnings.filterwarnings(\"ignore\")\n", "\n", "pd.set_option(\"display.max_columns\", None)\n", "pd.set_option(\"display.max_rows\", 100)\n", "pd.set_option(\"display.width\", 200)" ] }, { "cell_type": "markdown", "id": "98ed9cb8-7490-4513-b2ae-dd4a600cf055", "metadata": {}, "source": [ "# Load the survey dataset" ] }, { "cell_type": "code", "execution_count": 2, "id": "bdf7d046-d373-4b3e-b2c2-6bf42fc0d083", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Dataset shape: (102, 31)\n" ] }, { "data": { "text/html": [ "
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TimestampQ1. What is your current role?Q2. How many years of experience do you have in IT, cybersecurity or a related field?Q3. What type of organisation do you primarily work for?Q4. What is the approximate size of your organisation?Q5. Have you been involved in or exposed to cybersecurity incident response or digital evidence handling?OR1. Senior management provides sufficient support for digital forensic readiness within the organisation.OR2. The organisation allocates sufficient resources for activities related to digital evidence collection and investigation.OR3. Responsibilities for handling potential digital evidence are clearly defined within the organisation.OR4. Relevant departments cooperate effectively during cybersecurity incidents involving digital evidence.\\nOR5. The organisation considers digital forensic readiness when developing or reviewing its cybersecurity practices.TC1. The organisation maintains adequate logging of security-relevant activities across its IT systems.TC2. The organisation has effective mechanisms for monitoring activities that may provide useful digital evidence.TC3. The organisation has appropriate technical capabilities for collecting digital evidence during cyber incidents.TC4. Digital evidence can be securely stored and protected from unauthorised alteration or deletion.TC5. The organisation has access to appropriate forensic, monitoring or security technologies to support cyber incident investigations.EKS1. Employees have sufficient awareness of the importance of digital evidence during cybersecurity incidents.EKS2. Relevant employees receive adequate training on identifying potential digital evidence.EKS3. Relevant employees understand how digital evidence should be preserved during a cyber incident.EKS4. Employees know whom to contact when they identify information that may be relevant to a cybersecurity investigation.EKS5. Relevant employees have sufficient knowledge and skills to support the organisation's digital forensic activities.IRC1. The organisation can detect and identify cybersecurity incidents in a timely manner.IRC2. The organisation has clearly defined procedures for reporting cybersecurity incidents.IRC3. The organisation is able to contain cybersecurity incidents while protecting potentially valuable digital evidence.IRC4. The organisation can coordinate incident-response activities with digital evidence collection and preservation.IRC5. The organisation is capable of conducting or supporting investigations following cybersecurity incidents.DFR1. The organisation is well prepared to collect relevant digital evidence when a cybersecurity incident occurs.DFR2. The organisation is well prepared to preserve digital evidence for subsequent investigation.DFR3. The organisation can provide reliable digital evidence to support the investigation of cybersecurity incidents.DFR4. The organisation can respond effectively to digital evidence requirements during cybersecurity incidents.DFR5. Overall, the organisation has a high level of digital forensic readiness.
02026/09/10 1:48:36 pm GMT+5:30Incident Response/Security OperationsMore than 10 yearsPrivate sectorLargeNoStrongly AgreeStrongly DisagreeDisagreeNeutralDisagreeDisagreeNeutralDisagreeDisagreeAgreeDisagreeNeutralNeutralNeutralNeutralStrongly disagreeNeutralNeutralAgreeNeutralDisagreeNeutralNeutralStrongly agreeNeutral
12026/09/10 1:49:05 pm GMT+5:30Incident Response/Security Operations1–3 yearsPrivate sectorMediumYesDisagreeionNeutralNeutralAgreeNeutralDisagreeDisagreeDisagreeAgreeNeutralDisagreeNeutralNeutralAgreeDisagreeDisagreeDisagreeNeutralAgreeDisagreeDisagreeNeutralDisagreeNeutralStrongly disagree
22026/09/10 1:55:55 pm GMT+5:30Cybersecurity Professional4–6 yearsPrivate sectorSmallNoNeutralDisagreeDisagreeNeutralDisagreeNeutralDisagreeNeutralDisagreeNeutralNeutralNeutralNeutralNeutralDisagreeNeutralDisagreeDisagreeNeutralNeutralNeutralDisagreeNeutralDisagreeDisagree
32026/09/10 1:59:36 pm GMT+5:30Network/System Administrator1–3 yearsPrivate sectorSmallNoNeutralNeutralNeutralDisagreeNeutralNeutralDisagreeNeutralStrongly DisagreeNeutralNeutralDisagreeStrongly DisagreeDisagreeDisagreeDisagreeNeutralStrongly DisagreeStrongly DisagreeDisagreeNeutralDisagreeNeutralDisagreeDisagree
42026/09/10 2:00:53 pm GMT+5:30Incident Response/Security OperationsLess than 1 yearNon-profit organisationSmallYesNeutralDisagreeAgreeDisagreeDisagreeDisagreeDisagreeNeutralNeutralDisagreeDisagreeDisagreeNeutralDisagreeDisagreeAgreeStrongly agreeStrongly DisagreeDisagreeStrongly DisagreeNeutralDisagreeStrongly DisagreeStrongly disagreeStrongly disagree
\n", "
" ], "text/plain": [ " Timestamp Q1. What is your current role? Q2. How many years of experience do you have in IT, cybersecurity or a related field? \\\n", "0 2026/09/10 1:48:36 pm GMT+5:30 Incident Response/Security Operations More than 10 years \n", "1 2026/09/10 1:49:05 pm GMT+5:30 Incident Response/Security Operations 1–3 years \n", "2 2026/09/10 1:55:55 pm GMT+5:30 Cybersecurity Professional 4–6 years \n", "3 2026/09/10 1:59:36 pm GMT+5:30 Network/System Administrator 1–3 years \n", "4 2026/09/10 2:00:53 pm GMT+5:30 Incident Response/Security Operations Less than 1 year \n", "\n", " Q3. What type of organisation do you primarily work for? Q4. What is the approximate size of your organisation? \\\n", "0 Private sector Large \n", "1 Private sector Medium \n", "2 Private sector Small \n", "3 Private sector Small \n", "4 Non-profit organisation Small \n", "\n", " Q5. Have you been involved in or exposed to cybersecurity incident response or digital evidence handling? \\\n", "0 No \n", "1 Yes \n", "2 No \n", "3 No \n", "4 Yes \n", "\n", " OR1. Senior management provides sufficient support for digital forensic readiness within the organisation. \\\n", "0 Strongly Agree \n", "1 Disagreeion \n", "2 Neutral \n", "3 Neutral \n", "4 Neutral \n", "\n", " OR2. The organisation allocates sufficient resources for activities related to digital evidence collection and investigation. \\\n", "0 Strongly Disagree \n", "1 Neutral \n", "2 Disagree \n", "3 Neutral \n", "4 Disagree \n", "\n", " OR3. Responsibilities for handling potential digital evidence are clearly defined within the organisation. \\\n", "0 Disagree \n", "1 Neutral \n", "2 Disagree \n", "3 Neutral \n", "4 Agree \n", "\n", " OR4. Relevant departments cooperate effectively during cybersecurity incidents involving digital evidence.\\n \\\n", "0 Neutral \n", "1 Agree \n", "2 Neutral \n", "3 Disagree \n", "4 Disagree \n", "\n", " OR5. The organisation considers digital forensic readiness when developing or reviewing its cybersecurity practices. \\\n", "0 Disagree \n", "1 Neutral \n", "2 Disagree \n", "3 Neutral \n", "4 Disagree \n", "\n", " TC1. The organisation maintains adequate logging of security-relevant activities across its IT systems. \\\n", "0 Disagree \n", "1 Disagree \n", "2 Neutral \n", "3 Neutral \n", "4 Disagree \n", "\n", " TC2. The organisation has effective mechanisms for monitoring activities that may provide useful digital evidence. \\\n", "0 Neutral \n", "1 Disagree \n", "2 Disagree \n", "3 Disagree \n", "4 Disagree \n", "\n", " TC3. The organisation has appropriate technical capabilities for collecting digital evidence during cyber incidents. \\\n", "0 Disagree \n", "1 Disagree \n", "2 Neutral \n", "3 Neutral \n", "4 Neutral \n", "\n", " TC4. Digital evidence can be securely stored and protected from unauthorised alteration or deletion. \\\n", "0 Disagree \n", "1 Agree \n", "2 Disagree \n", "3 Strongly Disagree \n", "4 Neutral \n", "\n", " TC5. The organisation has access to appropriate forensic, monitoring or security technologies to support cyber incident investigations. \\\n", "0 Agree \n", "1 Neutral \n", "2 Neutral \n", "3 Neutral \n", "4 Disagree \n", "\n", " EKS1. Employees have sufficient awareness of the importance of digital evidence during cybersecurity incidents. \\\n", "0 Disagree \n", "1 Disagree \n", "2 Neutral \n", "3 Neutral \n", "4 Disagree \n", "\n", " EKS2. Relevant employees receive adequate training on identifying potential digital evidence. EKS3. Relevant employees understand how digital evidence should be preserved during a cyber incident. \\\n", "0 Neutral Neutral \n", "1 Neutral Neutral \n", "2 Neutral Neutral \n", "3 Disagree Strongly Disagree \n", "4 Disagree Neutral \n", "\n", " EKS4. Employees know whom to contact when they identify information that may be relevant to a cybersecurity investigation. \\\n", "0 Neutral \n", "1 Agree \n", "2 Neutral \n", "3 Disagree \n", "4 Disagree \n", "\n", " EKS5. Relevant employees have sufficient knowledge and skills to support the organisation's digital forensic activities. \\\n", "0 Neutral \n", "1 Disagree \n", "2 Disagree \n", "3 Disagree \n", "4 Disagree \n", "\n", " IRC1. The organisation can detect and identify cybersecurity incidents in a timely manner. IRC2. The organisation has clearly defined procedures for reporting cybersecurity incidents. \\\n", "0 Strongly disagree Neutral \n", "1 Disagree Disagree \n", "2 Neutral Disagree \n", "3 Disagree Neutral \n", "4 Agree Strongly agree \n", "\n", " IRC3. The organisation is able to contain cybersecurity incidents while protecting potentially valuable digital evidence. \\\n", "0 Neutral \n", "1 Neutral \n", "2 Disagree \n", "3 Strongly Disagree \n", "4 Strongly Disagree \n", "\n", " IRC4. The organisation can coordinate incident-response activities with digital evidence collection and preservation. \\\n", "0 Agree \n", "1 Agree \n", "2 Neutral \n", "3 Strongly Disagree \n", "4 Disagree \n", "\n", " IRC5. The organisation is capable of conducting or supporting investigations following cybersecurity incidents. \\\n", "0 Neutral \n", "1 Disagree \n", "2 Neutral \n", "3 Disagree \n", "4 Strongly Disagree \n", "\n", " DFR1. The organisation is well prepared to collect relevant digital evidence when a cybersecurity incident occurs. \\\n", "0 Disagree \n", "1 Disagree \n", "2 Neutral \n", "3 Neutral \n", "4 Neutral \n", "\n", " DFR2. The organisation is well prepared to preserve digital evidence for subsequent investigation. \\\n", "0 Neutral \n", "1 Neutral \n", "2 Disagree \n", "3 Disagree \n", "4 Disagree \n", "\n", " DFR3. The organisation can provide reliable digital evidence to support the investigation of cybersecurity incidents. \\\n", "0 Neutral \n", "1 Disagree \n", "2 Neutral \n", "3 Neutral \n", "4 Strongly Disagree \n", "\n", " DFR4. The organisation can respond effectively to digital evidence requirements during cybersecurity incidents. DFR5. Overall, the organisation has a high level of digital forensic readiness. \n", "0 Strongly agree Neutral \n", "1 Neutral Strongly disagree \n", "2 Disagree Disagree \n", "3 Disagree Disagree \n", "4 Strongly disagree Strongly disagree " ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "file_path = \"Survey Questionnaire.csv\"\n", "\n", "df = pd.read_csv(file_path)\n", "\n", "print(\"Dataset shape:\", df.shape)\n", "display(df.head())" ] }, { "cell_type": "markdown", "id": "8c27e777-234d-494c-b653-ac487c364ce5", "metadata": {}, "source": [ "# Inspect the dataset" ] }, { "cell_type": "code", "execution_count": 3, "id": "26d4ad2d-5e35-4e6f-bb89-3e7a64bcb683", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Number of rows: 102\n", "Number of columns: 31\n", "\n", "Column names:\n", "1 : Timestamp\n", "2 : Q1. What is your current role? \n", "3 : Q2. How many years of experience do you have in IT, cybersecurity or a related field? \n", "4 : Q3. What type of organisation do you primarily work for? \n", "5 : Q4. What is the approximate size of your organisation? \n", "6 : Q5. Have you been involved in or exposed to cybersecurity incident response or digital evidence handling? \n", "7 : OR1. Senior management provides sufficient support for digital forensic readiness within the organisation.\n", "8 : OR2. The organisation allocates sufficient resources for activities related to digital evidence collection and investigation.\n", "9 : OR3. Responsibilities for handling potential digital evidence are clearly defined within the organisation.\n", "10 : OR4. Relevant departments cooperate effectively during cybersecurity incidents involving digital evidence.\n", "\n", "11 : OR5. The organisation considers digital forensic readiness when developing or reviewing its cybersecurity practices.\n", "12 : TC1. The organisation maintains adequate logging of security-relevant activities across its IT systems.\n", "13 : TC2. The organisation has effective mechanisms for monitoring activities that may provide useful digital evidence.\n", "14 : TC3. The organisation has appropriate technical capabilities for collecting digital evidence during cyber incidents.\n", "15 : TC4. Digital evidence can be securely stored and protected from unauthorised alteration or deletion.\n", "16 : TC5. The organisation has access to appropriate forensic, monitoring or security technologies to support cyber incident investigations.\n", "17 : EKS1. Employees have sufficient awareness of the importance of digital evidence during cybersecurity incidents.\n", "18 : EKS2. Relevant employees receive adequate training on identifying potential digital evidence.\n", "19 : EKS3. Relevant employees understand how digital evidence should be preserved during a cyber incident.\n", "20 : EKS4. Employees know whom to contact when they identify information that may be relevant to a cybersecurity investigation.\n", "21 : EKS5. Relevant employees have sufficient knowledge and skills to support the organisation's digital forensic activities.\n", "22 : IRC1. The organisation can detect and identify cybersecurity incidents in a timely manner.\n", "23 : IRC2. The organisation has clearly defined procedures for reporting cybersecurity incidents.\n", "24 : IRC3. The organisation is able to contain cybersecurity incidents while protecting potentially valuable digital evidence.\n", "25 : IRC4. The organisation can coordinate incident-response activities with digital evidence collection and preservation.\n", "26 : IRC5. The organisation is capable of conducting or supporting investigations following cybersecurity incidents.\n", "27 : DFR1. The organisation is well prepared to collect relevant digital evidence when a cybersecurity incident occurs.\n", "28 : DFR2. The organisation is well prepared to preserve digital evidence for subsequent investigation.\n", "29 : DFR3. The organisation can provide reliable digital evidence to support the investigation of cybersecurity incidents.\n", "30 : DFR4. The organisation can respond effectively to digital evidence requirements during cybersecurity incidents.\n", "31 : DFR5. Overall, the organisation has a high level of digital forensic readiness.\n" ] } ], "source": [ "print(\"Number of rows:\", df.shape[0])\n", "print(\"Number of columns:\", df.shape[1])\n", "\n", "print(\"\\nColumn names:\")\n", "for i, col in enumerate(df.columns, start=1):\n", " print(i, \":\", col)" ] }, { "cell_type": "code", "execution_count": 4, "id": "4fd4f4a0-f51a-4ee5-b0f2-ddebb9de86dd", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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Missing_CountMissing_Percentage
Q5. Have you been involved in or exposed to cybersecurity incident response or digital evidence handling?21.960784
OR3. Responsibilities for handling potential digital evidence are clearly defined within the organisation.10.980392
OR4. Relevant departments cooperate effectively during cybersecurity incidents involving digital evidence.\\n10.980392
TC1. The organisation maintains adequate logging of security-relevant activities across its IT systems.10.980392
TC4. Digital evidence can be securely stored and protected from unauthorised alteration or deletion.10.980392
TC5. The organisation has access to appropriate forensic, monitoring or security technologies to support cyber incident investigations.10.980392
IRC5. The organisation is capable of conducting or supporting investigations following cybersecurity incidents.10.980392
DFR1. The organisation is well prepared to collect relevant digital evidence when a cybersecurity incident occurs.10.980392
DFR2. The organisation is well prepared to preserve digital evidence for subsequent investigation.10.980392
DFR3. The organisation can provide reliable digital evidence to support the investigation of cybersecurity incidents.10.980392
DFR4. The organisation can respond effectively to digital evidence requirements during cybersecurity incidents.10.980392
DFR5. Overall, the organisation has a high level of digital forensic readiness.21.960784
\n", "
" ], "text/plain": [ " Missing_Count Missing_Percentage\n", "Q5. Have you been involved in or exposed to cyb... 2 1.960784\n", "OR3. Responsibilities for handling potential di... 1 0.980392\n", "OR4. Relevant departments cooperate effectively... 1 0.980392\n", "TC1. The organisation maintains adequate loggin... 1 0.980392\n", "TC4. Digital evidence can be securely stored an... 1 0.980392\n", "TC5. The organisation has access to appropriate... 1 0.980392\n", "IRC5. The organisation is capable of conducting... 1 0.980392\n", "DFR1. The organisation is well prepared to coll... 1 0.980392\n", "DFR2. The organisation is well prepared to pres... 1 0.980392\n", "DFR3. The organisation can provide reliable dig... 1 0.980392\n", "DFR4. The organisation can respond effectively ... 1 0.980392\n", "DFR5. Overall, the organisation has a high leve... 2 1.960784" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Check missing values\n", "missing = pd.DataFrame({\n", " \"Missing_Count\": df.isnull().sum(),\n", " \"Missing_Percentage\": (df.isnull().sum() / len(df)) * 100\n", "})\n", "\n", "display(missing[missing[\"Missing_Count\"] > 0])" ] }, { "cell_type": "markdown", "id": "891a9516-b9bc-4125-99b8-68300da5b6d2", "metadata": {}, "source": [ "# Data Preprocessing " ] }, { "cell_type": "code", "execution_count": 5, "id": "4bf1e1b9-55da-4f5d-9a69-a0144f4a32fd", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Column standardisation completed.\n" ] }, { "data": { "text/html": [ "
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Original ColumnNew Column
0Q1. What is your current role?Q1_Role
1Q2. How many years of experience do you have ...Q2_Experience
2Q3. What type of organisation do you primaril...Q3_Organisation_Type
3Q4. What is the approximate size of your orga...Q4_Organisation_Size
4Q5. Have you been involved in or exposed to cy...Q5_Incident_Exposure
5OR1. Senior management provides sufficient sup...OR1
6OR2. The organisation allocates sufficient res...OR2
7OR3. Responsibilities for handling potential d...OR3
8OR4. Relevant departments cooperate effectivel...OR4
9OR5. The organisation considers digital forens...OR5
10TC1. The organisation maintains adequate loggi...TC1
11TC2. The organisation has effective mechanisms...TC2
12TC3. The organisation has appropriate technica...TC3
13TC4. Digital evidence can be securely stored a...TC4
14TC5. The organisation has access to appropriat...TC5
15EKS1. Employees have sufficient awareness of t...EKS1
16EKS2. Relevant employees receive adequate trai...EKS2
17EKS3. Relevant employees understand how digita...EKS3
18EKS4. Employees know whom to contact when they...EKS4
19EKS5. Relevant employees have sufficient knowl...EKS5
20IRC1. The organisation can detect and identify...IRC1
21IRC2. The organisation has clearly defined pro...IRC2
22IRC3. The organisation is able to contain cybe...IRC3
23IRC4. The organisation can coordinate incident...IRC4
24IRC5. The organisation is capable of conductin...IRC5
25DFR1. The organisation is well prepared to col...DFR1
26DFR2. The organisation is well prepared to pre...DFR2
27DFR3. The organisation can provide reliable di...DFR3
28DFR4. The organisation can respond effectively...DFR4
29DFR5. Overall, the organisation has a high lev...DFR5
\n", "
" ], "text/plain": [ " Original Column New Column\n", "0 Q1. What is your current role? Q1_Role\n", "1 Q2. How many years of experience do you have ... Q2_Experience\n", "2 Q3. What type of organisation do you primaril... Q3_Organisation_Type\n", "3 Q4. What is the approximate size of your orga... Q4_Organisation_Size\n", "4 Q5. Have you been involved in or exposed to cy... Q5_Incident_Exposure\n", "5 OR1. Senior management provides sufficient sup... OR1\n", "6 OR2. The organisation allocates sufficient res... OR2\n", "7 OR3. Responsibilities for handling potential d... OR3\n", "8 OR4. Relevant departments cooperate effectivel... OR4\n", "9 OR5. The organisation considers digital forens... OR5\n", "10 TC1. The organisation maintains adequate loggi... TC1\n", "11 TC2. The organisation has effective mechanisms... TC2\n", "12 TC3. The organisation has appropriate technica... TC3\n", "13 TC4. Digital evidence can be securely stored a... TC4\n", "14 TC5. The organisation has access to appropriat... TC5\n", "15 EKS1. Employees have sufficient awareness of t... EKS1\n", "16 EKS2. Relevant employees receive adequate trai... EKS2\n", "17 EKS3. Relevant employees understand how digita... EKS3\n", "18 EKS4. Employees know whom to contact when they... EKS4\n", "19 EKS5. Relevant employees have sufficient knowl... EKS5\n", "20 IRC1. The organisation can detect and identify... IRC1\n", "21 IRC2. The organisation has clearly defined pro... IRC2\n", "22 IRC3. The organisation is able to contain cybe... IRC3\n", "23 IRC4. The organisation can coordinate incident... IRC4\n", "24 IRC5. The organisation is capable of conductin... IRC5\n", "25 DFR1. The organisation is well prepared to col... DFR1\n", "26 DFR2. The organisation is well prepared to pre... DFR2\n", "27 DFR3. The organisation can provide reliable di... DFR3\n", "28 DFR4. The organisation can respond effectively... DFR4\n", "29 DFR5. Overall, the organisation has a high lev... DFR5" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Standardise column names \n", "def identify_question_column(columns, prefix):\n", " \"\"\"\n", " Find the first column beginning with the specified prefix.\n", " \"\"\"\n", " matches = [\n", " col for col in columns\n", " if str(col).strip().upper().startswith(prefix.upper())\n", " ]\n", "\n", " if not matches:\n", " raise ValueError(\n", " f\"Could not find a column beginning with '{prefix}'.\"\n", " )\n", "\n", " return matches[0]\n", "\n", "\n", "# Work with stripped versions for identification\n", "original_columns = list(df.columns)\n", "\n", "column_mapping = {}\n", "\n", "# Demographic questions\n", "column_mapping[identify_question_column(df.columns, \"Q1.\")] = \"Q1_Role\"\n", "column_mapping[identify_question_column(df.columns, \"Q2.\")] = \"Q2_Experience\"\n", "column_mapping[identify_question_column(df.columns, \"Q3.\")] = \"Q3_Organisation_Type\"\n", "column_mapping[identify_question_column(df.columns, \"Q4.\")] = \"Q4_Organisation_Size\"\n", "column_mapping[identify_question_column(df.columns, \"Q5.\")] = \"Q5_Incident_Exposure\"\n", "\n", "\n", "# Likert constructs\n", "for construct in [\"OR\", \"TC\", \"EKS\", \"IRC\", \"DFR\"]:\n", "\n", " for i in range(1, 6):\n", "\n", " prefix = f\"{construct}{i}.\"\n", "\n", " matches = [\n", " col for col in df.columns\n", " if str(col).strip().upper().startswith(prefix.upper())\n", " ]\n", "\n", " if not matches:\n", " raise ValueError(\n", " f\"Could not find questionnaire item {construct}{i}.\"\n", " )\n", "\n", " column_mapping[matches[0]] = f\"{construct}{i}\"\n", "\n", "\n", "df = df.rename(columns=column_mapping)\n", "\n", "print(\"Column standardisation completed.\")\n", "\n", "display(pd.DataFrame({\n", " \"Original Column\": column_mapping.keys(),\n", " \"New Column\": column_mapping.values()\n", "}))" ] }, { "cell_type": "code", "execution_count": 6, "id": "058b3c90-6af8-4078-a17c-34d2936a7d88", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "All expected questionnaire variables are present.\n" ] } ], "source": [ "# Check that all expected variables exist\n", "demographic_columns = [\n", " \"Q1_Role\",\n", " \"Q2_Experience\",\n", " \"Q3_Organisation_Type\",\n", " \"Q4_Organisation_Size\",\n", " \"Q5_Incident_Exposure\"\n", "]\n", "\n", "construct_items = {\n", " \"OR\": [f\"OR{i}\" for i in range(1, 6)],\n", " \"TC\": [f\"TC{i}\" for i in range(1, 6)],\n", " \"EKS\": [f\"EKS{i}\" for i in range(1, 6)],\n", " \"IRC\": [f\"IRC{i}\" for i in range(1, 6)],\n", " \"DFR\": [f\"DFR{i}\" for i in range(1, 6)]\n", "}\n", "\n", "expected_columns = (\n", " demographic_columns +\n", " [item for items in construct_items.values() for item in items]\n", ")\n", "\n", "missing_expected = [\n", " col for col in expected_columns\n", " if col not in df.columns\n", "]\n", "\n", "if missing_expected:\n", " raise ValueError(\n", " \"The following expected columns are missing:\\n\"\n", " + \"\\n\".join(missing_expected)\n", " )\n", "\n", "print(\"All expected questionnaire variables are present.\")" ] }, { "cell_type": "code", "execution_count": 7, "id": "37daa3ff-ffce-4418-abce-99a9055f3e94", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "IMPORTANT METHODOLOGICAL NOTE:\n", "No separate Forensic Policy (FP) questionnaire items were detected in the supplied dataset.\n", "\n", "Therefore, this analysis will NOT create or invent an FP variable from OR, TC, EKS or IRC.\n", "\n", "Current inferential model:\n", "DFR = OR + TC + EKS + IRC\n" ] } ], "source": [ "# Check for a separate Forensic Policy construct\n", "possible_fp_columns = [\n", " col for col in df.columns\n", " if str(col).strip().upper().startswith(\"FP\")\n", "]\n", "\n", "if possible_fp_columns:\n", " print(\"Forensic Policy variables detected:\")\n", " print(possible_fp_columns)\n", "\n", " print(\n", " \"\\nFP variables can be incorporated into the inferential \"\n", " \"analysis if they represent a separate validated construct.\"\n", " )\n", "\n", "else:\n", " print(\n", " \"IMPORTANT METHODOLOGICAL NOTE:\\n\"\n", " \"No separate Forensic Policy (FP) questionnaire items were \"\n", " \"detected in the supplied dataset.\"\n", " )\n", "\n", " print(\n", " \"\\nTherefore, this analysis will NOT create or invent an FP \"\n", " \"variable from OR, TC, EKS or IRC.\"\n", " )\n", "\n", " print(\n", " \"\\nCurrent inferential model:\"\n", " \"\\nDFR = OR + TC + EKS + IRC\"\n", " )" ] }, { "cell_type": "code", "execution_count": 8, "id": "f1e054ff-2e1a-4df6-b460-a6252400c4d4", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Final shape after structural cleaning: (102, 30)\n" ] } ], "source": [ "# Remove unnecessary columns\n", "if \"Timestamp\" in df.columns:\n", " df = df.drop(columns=[\"Timestamp\"])\n", "\n", "# Remove completely empty columns\n", "df = df.dropna(axis=1, how=\"all\")\n", "\n", "print(\"Final shape after structural cleaning:\", df.shape)" ] }, { "cell_type": "code", "execution_count": 9, "id": "3c4ed0cd-365b-4e56-bf7b-577d1ab2dc42", "metadata": {}, "outputs": [], "source": [ "# Clean text responses\n", "def clean_text(value):\n", " if pd.isna(value):\n", " return value\n", " \n", " value = str(value).strip()\n", " \n", " # Correct known data-entry error\n", " value = value.replace(\"Disagreeion\", \"Disagree\")\n", " \n", " # Standardise capitalisation\n", " value_lower = value.lower()\n", " \n", " mapping = {\n", " \"strongly disagree\": \"Strongly Disagree\",\n", " \"disagree\": \"Disagree\",\n", " \"neutral\": \"Neutral\",\n", " \"agree\": \"Agree\",\n", " \"strongly agree\": \"Strongly Agree\"\n", " }\n", " \n", " return mapping.get(value_lower, value)\n", "\n", "\n", "likert_columns = (\n", " [f\"OR{i}\" for i in range(1, 6)] +\n", " [f\"TC{i}\" for i in range(1, 6)] +\n", " [f\"EKS{i}\" for i in range(1, 6)] +\n", " [f\"IRC{i}\" for i in range(1, 6)] +\n", " [f\"DFR{i}\" for i in range(1, 6)]\n", ")\n", "\n", "for col in likert_columns:\n", " df[col] = df[col].apply(clean_text)" ] }, { "cell_type": "code", "execution_count": 10, "id": "24346684-9097-4df8-8bc0-51fd842d3ce0", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "OR1\n", "OR1\n", "Strongly Disagree 29\n", "Agree 27\n", "Neutral 22\n", "Disagree 15\n", "Strongly Agree 9\n", "Name: count, dtype: int64\n", "\n", "OR2\n", "OR2\n", "Agree 46\n", "Disagree 18\n", "Strongly Disagree 17\n", "Neutral 17\n", "Strongly Agree 4\n", "Name: count, dtype: int64\n", "\n", "OR3\n", "OR3\n", "Agree 37\n", "Strongly Disagree 20\n", "Disagree 17\n", "Neutral 17\n", "Strongly Agree 10\n", "NaN 1\n", "Name: count, dtype: int64\n", "\n", "OR4\n", "OR4\n", "Agree 57\n", "Neutral 14\n", "Strongly Disagree 14\n", "Strongly Agree 12\n", "Disagree 4\n", "NaN 1\n", "Name: count, dtype: int64\n", "\n", "OR5\n", "OR5\n", "Agree 41\n", "Strongly Agree 24\n", "Strongly Disagree 16\n", "Neutral 11\n", "Disagree 10\n", "Name: count, dtype: int64\n", "\n", "TC1\n", "TC1\n", "Agree 30\n", "Strongly Disagree 27\n", "Strongly Agree 17\n", "Disagree 14\n", "Neutral 13\n", "NaN 1\n", "Name: count, dtype: int64\n", "\n", "TC2\n", "TC2\n", "Agree 52\n", "Strongly Disagree 17\n", "Strongly Agree 13\n", "Disagree 11\n", "Neutral 9\n", "Name: count, dtype: int64\n", "\n", "TC3\n", "TC3\n", "Agree 40\n", "Neutral 19\n", "Strongly Disagree 15\n", "Disagree 14\n", "Strongly Agree 14\n", "Name: count, dtype: int64\n", "\n", "TC4\n", "TC4\n", "Agree 54\n", "Strongly Agree 21\n", "Disagree 12\n", "Neutral 8\n", "Strongly Disagree 6\n", "NaN 1\n", "Name: count, dtype: int64\n", "\n", "TC5\n", "TC5\n", "Agree 39\n", "Strongly Agree 26\n", "Strongly Disagree 17\n", "Neutral 10\n", "Disagree 9\n", "NaN 1\n", "Name: count, dtype: int64\n", "\n", "EKS1\n", "EKS1\n", "Strongly Disagree 39\n", "Agree 26\n", "Neutral 16\n", "Disagree 11\n", "Strongly Agree 10\n", "Name: count, dtype: int64\n", "\n", "EKS2\n", "EKS2\n", "Agree 46\n", "Neutral 16\n", "Strongly Agree 15\n", "Disagree 13\n", "Strongly Disagree 12\n", "Name: count, dtype: int64\n", "\n", "EKS3\n", "EKS3\n", "Agree 41\n", "Neutral 17\n", "Strongly Disagree 16\n", "Strongly Agree 16\n", "Disagree 12\n", "Name: count, dtype: int64\n", "\n", "EKS4\n", "EKS4\n", "Agree 54\n", "Strongly Agree 18\n", "Strongly Disagree 14\n", "Neutral 9\n", "Disagree 7\n", "Name: count, dtype: int64\n", "\n", "EKS5\n", "EKS5\n", "Agree 40\n", "Strongly Agree 22\n", "Strongly Disagree 19\n", "Disagree 14\n", "Neutral 7\n", "Name: count, dtype: int64\n", "\n", "IRC1\n", "IRC1\n", "Strongly Disagree 33\n", "Agree 25\n", "Strongly Agree 18\n", "Disagree 14\n", "Neutral 12\n", "Name: count, dtype: int64\n", "\n", "IRC2\n", "IRC2\n", "Agree 49\n", "Disagree 15\n", "Strongly Disagree 15\n", "Strongly Agree 14\n", "Neutral 9\n", "Name: count, dtype: int64\n", "\n", "IRC3\n", "IRC3\n", "Agree 37\n", "Neutral 26\n", "Strongly Disagree 19\n", "Strongly Agree 11\n", "Disagree 9\n", "Name: count, dtype: int64\n", "\n", "IRC4\n", "IRC4\n", "Agree 50\n", "Strongly Agree 17\n", "Strongly Disagree 16\n", "Disagree 16\n", "Neutral 3\n", "Name: count, dtype: int64\n", "\n", "IRC5\n", "IRC5\n", "Agree 45\n", "Strongly Agree 19\n", "Strongly Disagree 13\n", "Neutral 12\n", "Disagree 12\n", "NaN 1\n", "Name: count, dtype: int64\n", "\n", "DFR1\n", "DFR1\n", "Strongly Disagree 34\n", "Agree 26\n", "Neutral 15\n", "Strongly Agree 15\n", "Disagree 11\n", "NaN 1\n", "Name: count, dtype: int64\n", "\n", "DFR2\n", "DFR2\n", "Agree 45\n", "Disagree 17\n", "Neutral 16\n", "Strongly Agree 14\n", "Strongly Disagree 9\n", "NaN 1\n", "Name: count, dtype: int64\n", "\n", "DFR3\n", "DFR3\n", "Agree 36\n", "Neutral 20\n", "Strongly Agree 20\n", "Strongly Disagree 16\n", "Disagree 9\n", "NaN 1\n", "Name: count, dtype: int64\n", "\n", "DFR4\n", "DFR4\n", "Agree 50\n", "Strongly Agree 18\n", "Strongly Disagree 14\n", "Disagree 10\n", "Neutral 9\n", "NaN 1\n", "Name: count, dtype: int64\n", "\n", "DFR5\n", "DFR5\n", "Agree 39\n", "Strongly Agree 24\n", "Strongly Disagree 22\n", "Neutral 8\n", "Disagree 7\n", "NaN 2\n", "Name: count, dtype: int64\n" ] } ], "source": [ "# Verify the values\n", "for col in likert_columns:\n", " print(f\"\\n{col}\")\n", " print(df[col].value_counts(dropna=False))" ] }, { "cell_type": "code", "execution_count": 11, "id": "1334271d-1e59-4c34-bde5-8618179ac0fc", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Likert responses cleaned.\n" ] } ], "source": [ "# Clean Likert responses\n", "likert_columns = [\n", " item\n", " for items in construct_items.values()\n", " for item in items\n", "]\n", "\n", "likert_clean_mapping = {\n", " \"strongly disagree\": \"Strongly Disagree\",\n", " \"disagree\": \"Disagree\",\n", " \"neutral\": \"Neutral\",\n", " \"agree\": \"Agree\",\n", " \"strongly agree\": \"Strongly Agree\"\n", "}\n", "\n", "\n", "def clean_likert(value):\n", "\n", " if pd.isna(value):\n", " return np.nan\n", "\n", " value = str(value).strip()\n", "\n", " # Correct known data-entry error\n", " value = value.replace(\"Disagreeion\", \"Disagree\")\n", "\n", " # Standardise case\n", " value_lower = value.lower()\n", "\n", " return likert_clean_mapping.get(value_lower, value)\n", "\n", "\n", "for col in likert_columns:\n", " df[col] = df[col].apply(clean_likert)\n", "\n", "\n", "print(\"Likert responses cleaned.\")" ] }, { "cell_type": "code", "execution_count": 12, "id": "c157b203-a1df-4a36-afa5-4dff8f2d1769", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "No invalid Likert responses detected after standardisation.\n" ] } ], "source": [ "# Check for invalid Likert responses\n", "valid_likert_values = [\n", " \"Strongly Disagree\",\n", " \"Disagree\",\n", " \"Neutral\",\n", " \"Agree\",\n", " \"Strongly Agree\"\n", "]\n", "\n", "invalid_response_summary = {}\n", "\n", "for col in likert_columns:\n", "\n", " invalid_values = (\n", " df.loc[\n", " df[col].notna() &\n", " ~df[col].isin(valid_likert_values),\n", " col\n", " ]\n", " .value_counts()\n", " )\n", "\n", " if len(invalid_values) > 0:\n", " invalid_response_summary[col] = invalid_values\n", "\n", "\n", "if invalid_response_summary:\n", "\n", " print(\"Invalid Likert responses detected:\\n\")\n", "\n", " for col, values in invalid_response_summary.items():\n", " print(f\"{col}:\")\n", " print(values)\n", " print()\n", "\n", "else:\n", "\n", " print(\n", " \"No invalid Likert responses detected after \"\n", " \"standardisation.\"\n", " )" ] }, { "cell_type": "code", "execution_count": 13, "id": "e6722112-09ef-4433-a098-69c3c623bf8f", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Likert coding completed.\n" ] }, { "data": { "text/html": [ "
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" ], "text/plain": [ " OR1_score OR2_score OR3_score OR4_score OR5_score TC1_score TC2_score TC3_score TC4_score TC5_score EKS1_score EKS2_score EKS3_score EKS4_score EKS5_score IRC1_score IRC2_score \\\n", "0 5 1 2.0 3.0 2 2.0 3 2 2.0 4.0 2 3 3 3 3 1 3 \n", "1 2 3 3.0 4.0 3 2.0 2 2 4.0 3.0 2 3 3 4 2 2 2 \n", "2 3 2 2.0 3.0 2 3.0 2 3 2.0 3.0 3 3 3 3 2 3 2 \n", "3 3 3 3.0 2.0 3 3.0 2 3 1.0 3.0 3 2 1 2 2 2 3 \n", "4 3 2 4.0 2.0 2 2.0 2 3 3.0 2.0 2 2 3 2 2 4 5 \n", "\n", " IRC3_score IRC4_score IRC5_score DFR1_score DFR2_score DFR3_score DFR4_score DFR5_score \n", "0 3 4 3.0 2.0 3.0 3.0 5.0 3.0 \n", "1 3 4 2.0 2.0 3.0 2.0 3.0 1.0 \n", "2 2 3 3.0 3.0 2.0 3.0 2.0 2.0 \n", "3 1 1 2.0 3.0 2.0 3.0 2.0 2.0 \n", "4 1 2 1.0 3.0 2.0 1.0 1.0 1.0 " ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Convert Likert responses to numerical scores\n", "likert_mapping = {\n", " \"Strongly Disagree\": 1,\n", " \"Disagree\": 2,\n", " \"Neutral\": 3,\n", " \"Agree\": 4,\n", " \"Strongly Agree\": 5\n", "}\n", "\n", "score_columns = []\n", "\n", "for col in likert_columns:\n", "\n", " score_col = f\"{col}_score\"\n", "\n", " df[score_col] = df[col].map(likert_mapping)\n", "\n", " score_columns.append(score_col)\n", "\n", "\n", "print(\"Likert coding completed.\")\n", "\n", "display(df[score_columns].head())" ] }, { "cell_type": "code", "execution_count": 14, "id": "98bd3108-4e24-4fb7-91d2-600ae7858e2b", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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VariableMissing_CountMissing_Percentage
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3OR4_score10.980392
5TC1_score10.980392
8TC4_score10.980392
9TC5_score10.980392
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20DFR1_score10.980392
21DFR2_score10.980392
22DFR3_score10.980392
23DFR4_score10.980392
24DFR5_score21.960784
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" ], "text/plain": [ " Variable Missing_Count Missing_Percentage\n", "2 OR3_score 1 0.980392\n", "3 OR4_score 1 0.980392\n", "5 TC1_score 1 0.980392\n", "8 TC4_score 1 0.980392\n", "9 TC5_score 1 0.980392\n", "19 IRC5_score 1 0.980392\n", "20 DFR1_score 1 0.980392\n", "21 DFR2_score 1 0.980392\n", "22 DFR3_score 1 0.980392\n", "23 DFR4_score 1 0.980392\n", "24 DFR5_score 2 1.960784" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Total missing Likert responses: 12\n" ] } ], "source": [ "# Missing-value analysis\n", "missing_summary = pd.DataFrame({\n", " \"Variable\": score_columns,\n", " \"Missing_Count\": [\n", " df[col].isna().sum()\n", " for col in score_columns\n", " ]\n", "})\n", "\n", "missing_summary[\"Missing_Percentage\"] = (\n", " missing_summary[\"Missing_Count\"] /\n", " len(df) * 100\n", ")\n", "\n", "display(\n", " missing_summary[\n", " missing_summary[\"Missing_Count\"] > 0\n", " ]\n", ")\n", "\n", "print(\n", " \"Total missing Likert responses:\",\n", " int(missing_summary[\"Missing_Count\"].sum())\n", ")" ] }, { "cell_type": "code", "execution_count": 15, "id": "8423572c-3db2-445f-ad23-3767e96d0326", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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OR_ScoreTC_ScoreEKS_ScoreIRC_ScoreDFR_Score
02.62.62.82.83.2
13.02.62.82.62.2
22.42.62.82.62.4
32.82.42.01.82.4
42.62.42.22.61.6
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" ], "text/plain": [ " OR_Score TC_Score EKS_Score IRC_Score DFR_Score\n", "0 2.6 2.6 2.8 2.8 3.2\n", "1 3.0 2.6 2.8 2.6 2.2\n", "2 2.4 2.6 2.8 2.6 2.4\n", "3 2.8 2.4 2.0 1.8 2.4\n", "4 2.6 2.4 2.2 2.6 1.6" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Missing-data decision rule\n", "def calculate_construct_score(data, items, minimum_valid=4):\n", "\n", " valid_count = data[items].notna().sum(axis=1)\n", "\n", " score = data[items].mean(axis=1)\n", "\n", " score[valid_count < minimum_valid] = np.nan\n", "\n", " return score\n", "\n", "\n", "# Create construct scores\n", "for construct, items in construct_items.items():\n", "\n", " df[f\"{construct}_Score\"] = calculate_construct_score(\n", " df,\n", " items=[f\"{item}_score\" for item in items],\n", " minimum_valid=4\n", " )\n", "\n", "\n", "construct_score_columns = [\n", " \"OR_Score\",\n", " \"TC_Score\",\n", " \"EKS_Score\",\n", " \"IRC_Score\",\n", " \"DFR_Score\"\n", "]\n", "\n", "display(df[construct_score_columns].head())" ] }, { "cell_type": "code", "execution_count": 16, "id": "b0a96350-d57c-48b8-bcc7-08a3197c56a0", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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ConstructValid_NMissing_NValid_Percentage
0OR_Score1020100.0
1TC_Score1020100.0
2EKS_Score1020100.0
3IRC_Score1020100.0
4DFR_Score1020100.0
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" ], "text/plain": [ " Construct Valid_N Missing_N Valid_Percentage\n", "0 OR_Score 102 0 100.0\n", "1 TC_Score 102 0 100.0\n", "2 EKS_Score 102 0 100.0\n", "3 IRC_Score 102 0 100.0\n", "4 DFR_Score 102 0 100.0" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Report number of valid construct scores\n", "construct_validity = pd.DataFrame({\n", " \"Construct\": construct_score_columns,\n", " \"Valid_N\": [\n", " df[col].notna().sum()\n", " for col in construct_score_columns\n", " ],\n", " \"Missing_N\": [\n", " df[col].isna().sum()\n", " for col in construct_score_columns\n", " ]\n", "})\n", "\n", "construct_validity[\"Valid_Percentage\"] = (\n", " construct_validity[\"Valid_N\"] /\n", " len(df) * 100\n", ")\n", "\n", "display(construct_validity)" ] }, { "cell_type": "code", "execution_count": 17, "id": "187a7e68-e054-4101-8b18-bb06e2b3e01b", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Reverse-coded items specified in the questionnaire: []\n", "No reverse coding applied because all supplied Likert items are positively worded.\n" ] } ], "source": [ "# Reverse-coding check\n", "reverse_coded_items = []\n", "\n", "print(\n", " \"Reverse-coded items specified in the questionnaire:\",\n", " reverse_coded_items\n", ")\n", "\n", "if len(reverse_coded_items) == 0:\n", "\n", " print(\n", " \"No reverse coding applied because all supplied \"\n", " \"Likert items are positively worded.\"\n", " )\n", "\n", "else:\n", "\n", " for col in reverse_coded_items:\n", "\n", " df[f\"{col}_score\"] = (\n", " 6 - df[f\"{col}_score\"]\n", " )" ] }, { "cell_type": "markdown", "id": "2855047a-bc9d-4e36-8d85-d5ccb254f94b", "metadata": {}, "source": [ "# Descriptive statistics — individual items" ] }, { "cell_type": "code", "execution_count": 18, "id": "d21ed3d9-590c-41aa-b905-520f9092a6c7", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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NMeanSDMinimumMaximum
OR11022.7251.3581.05.0
OR21023.0201.2101.05.0
OR31013.0001.3191.05.0
OR41013.4851.1881.05.0
OR51023.4611.3691.05.0
TC11012.9601.4831.05.0
TC21023.3241.3061.05.0
TC31023.2351.2761.05.0
TC41013.7131.1081.05.0
TC51013.4751.4041.05.0
EKS11022.5781.4591.05.0
EKS21023.3821.2271.05.0
EKS31023.2841.3081.05.0
EKS41023.5391.2561.05.0
EKS51023.3141.4351.05.0
IRC11022.8141.5401.05.0
IRC21023.3141.2971.05.0
IRC31023.1181.2771.05.0
IRC41023.3531.3541.05.0
IRC51013.4461.2841.05.0
DFR11012.7721.5091.05.0
DFR21013.3761.1821.05.0
DFR31013.3471.3301.05.0
DFR41013.4751.2851.05.0
DFR51003.3601.4811.05.0
\n", "
" ], "text/plain": [ " N Mean SD Minimum Maximum\n", "OR1 102 2.725 1.358 1.0 5.0\n", "OR2 102 3.020 1.210 1.0 5.0\n", "OR3 101 3.000 1.319 1.0 5.0\n", "OR4 101 3.485 1.188 1.0 5.0\n", "OR5 102 3.461 1.369 1.0 5.0\n", "TC1 101 2.960 1.483 1.0 5.0\n", "TC2 102 3.324 1.306 1.0 5.0\n", "TC3 102 3.235 1.276 1.0 5.0\n", "TC4 101 3.713 1.108 1.0 5.0\n", "TC5 101 3.475 1.404 1.0 5.0\n", "EKS1 102 2.578 1.459 1.0 5.0\n", "EKS2 102 3.382 1.227 1.0 5.0\n", "EKS3 102 3.284 1.308 1.0 5.0\n", "EKS4 102 3.539 1.256 1.0 5.0\n", "EKS5 102 3.314 1.435 1.0 5.0\n", "IRC1 102 2.814 1.540 1.0 5.0\n", "IRC2 102 3.314 1.297 1.0 5.0\n", "IRC3 102 3.118 1.277 1.0 5.0\n", "IRC4 102 3.353 1.354 1.0 5.0\n", "IRC5 101 3.446 1.284 1.0 5.0\n", "DFR1 101 2.772 1.509 1.0 5.0\n", "DFR2 101 3.376 1.182 1.0 5.0\n", "DFR3 101 3.347 1.330 1.0 5.0\n", "DFR4 101 3.475 1.285 1.0 5.0\n", "DFR5 100 3.360 1.481 1.0 5.0" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# ITEM-LEVEL DESCRIPTIVE STATISTICS\n", "item_descriptive = pd.DataFrame({\n", " \"N\": [\n", " df[f\"{item}_score\"].count()\n", " for item in likert_columns\n", " ],\n", " \"Mean\": [\n", " df[f\"{item}_score\"].mean()\n", " for item in likert_columns\n", " ],\n", " \"SD\": [\n", " df[f\"{item}_score\"].std()\n", " for item in likert_columns\n", " ],\n", " \"Minimum\": [\n", " df[f\"{item}_score\"].min()\n", " for item in likert_columns\n", " ],\n", " \"Maximum\": [\n", " df[f\"{item}_score\"].max()\n", " for item in likert_columns\n", " ]\n", "}, index=likert_columns)\n", "\n", "display(item_descriptive.round(3))" ] }, { "cell_type": "code", "execution_count": 19, "id": "b3bc33d5-a041-434d-aee5-61dae858f634", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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NMeanSDMinimumMaximum
Organisational Readiness1023.1350.7401.84.8
Technical Capability1023.3400.7631.85.0
Employee Knowledge and Skills1023.2200.8221.05.0
Incident Response Capability1023.2080.8061.05.0
Digital Forensic Readiness1023.2620.8241.05.0
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" ], "text/plain": [ " N Mean SD Minimum Maximum\n", "Organisational Readiness 102 3.135 0.740 1.8 4.8\n", "Technical Capability 102 3.340 0.763 1.8 5.0\n", "Employee Knowledge and Skills 102 3.220 0.822 1.0 5.0\n", "Incident Response Capability 102 3.208 0.806 1.0 5.0\n", "Digital Forensic Readiness 102 3.262 0.824 1.0 5.0" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# CONSTRUCT-LEVEL DESCRIPTIVE STATISTICS\n", "construct_descriptive = pd.DataFrame({\n", " \"N\": df[construct_score_columns].count(),\n", " \"Mean\": df[construct_score_columns].mean(),\n", " \"SD\": df[construct_score_columns].std(),\n", " \"Minimum\": df[construct_score_columns].min(),\n", " \"Maximum\": df[construct_score_columns].max()\n", "})\n", "\n", "construct_descriptive.index = [\n", " \"Organisational Readiness\",\n", " \"Technical Capability\",\n", " \"Employee Knowledge and Skills\",\n", " \"Incident Response Capability\",\n", " \"Digital Forensic Readiness\"\n", "]\n", "\n", "display(construct_descriptive.round(3))" ] }, { "cell_type": "code", "execution_count": 20, "id": "ab5b40d0-1560-4e01-99e1-6e67bd7323c1", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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NMeanSDMinimumMaximumInterpretation
Organisational Readiness1023.1350.7401.84.8Moderate
Technical Capability1023.3400.7631.85.0Moderate
Employee Knowledge and Skills1023.2200.8221.05.0Moderate
Incident Response Capability1023.2080.8061.05.0Moderate
Digital Forensic Readiness1023.2620.8241.05.0Moderate
\n", "
" ], "text/plain": [ " N Mean SD Minimum Maximum Interpretation\n", "Organisational Readiness 102 3.135 0.740 1.8 4.8 Moderate\n", "Technical Capability 102 3.340 0.763 1.8 5.0 Moderate\n", "Employee Knowledge and Skills 102 3.220 0.822 1.0 5.0 Moderate\n", "Incident Response Capability 102 3.208 0.806 1.0 5.0 Moderate\n", "Digital Forensic Readiness 102 3.262 0.824 1.0 5.0 Moderate" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Interpret construct means\n", "def interpret_mean(mean):\n", "\n", " if pd.isna(mean):\n", " return \"Not available\"\n", "\n", " elif mean < 1.80:\n", " return \"Very Low\"\n", "\n", " elif mean < 2.60:\n", " return \"Low\"\n", "\n", " elif mean < 3.40:\n", " return \"Moderate\"\n", "\n", " elif mean < 4.20:\n", " return \"High\"\n", "\n", " else:\n", " return \"Very High\"\n", "\n", "\n", "construct_descriptive[\"Interpretation\"] = (\n", " construct_descriptive[\"Mean\"]\n", " .apply(interpret_mean)\n", ")\n", "\n", "display(construct_descriptive.round(3))" ] }, { "cell_type": "markdown", "id": "3d5b1420-1680-4a48-ba29-e95ff6a8209e", "metadata": {}, "source": [ "# Demographic frequency and percentage tables" ] }, { "cell_type": "code", "execution_count": 21, "id": "0b5cc738-8d67-4d0a-ad5a-fe5e60160a1a", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "============================================================\n", "Q1_Role\n", "============================================================\n" ] }, { "data": { "text/html": [ "
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FrequencyPercentage
Q1_Role
Incident Response/Security Operations2625.49
Cybersecurity Professional2221.57
Network/System Administrator2120.59
IT Management1918.63
IT/Systems Professional1312.75
Other10.98
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" ], "text/plain": [ " Frequency Percentage\n", "Q1_Role \n", "Incident Response/Security Operations 26 25.49\n", "Cybersecurity Professional 22 21.57\n", "Network/System Administrator 21 20.59\n", "IT Management 19 18.63\n", "IT/Systems Professional 13 12.75\n", "Other 1 0.98" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "\n", "============================================================\n", "Q2_Experience\n", "============================================================\n" ] }, { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
FrequencyPercentage
Q2_Experience
4–6 years3231.37
1–3 years2827.45
7–10 years2726.47
Less than 1 year98.82
More than 10 years65.88
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" ], "text/plain": [ " Frequency Percentage\n", "Q2_Experience \n", "4–6 years 32 31.37\n", "1–3 years 28 27.45\n", "7–10 years 27 26.47\n", "Less than 1 year 9 8.82\n", "More than 10 years 6 5.88" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "\n", "============================================================\n", "Q3_Organisation_Type\n", "============================================================\n" ] }, { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
FrequencyPercentage
Q3_Organisation_Type
Non-profit organisation4544.12
Private sector3231.37
Educational institution2120.59
Public sector43.92
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" ], "text/plain": [ " Frequency Percentage\n", "Q3_Organisation_Type \n", "Non-profit organisation 45 44.12\n", "Private sector 32 31.37\n", "Educational institution 21 20.59\n", "Public sector 4 3.92" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "\n", "============================================================\n", "Q4_Organisation_Size\n", "============================================================\n" ] }, { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
FrequencyPercentage
Q4_Organisation_Size
Large4443.14
Medium3130.39
Very large1413.73
Small1312.75
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" ], "text/plain": [ " Frequency Percentage\n", "Q4_Organisation_Size \n", "Large 44 43.14\n", "Medium 31 30.39\n", "Very large 14 13.73\n", "Small 13 12.75" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "\n", "============================================================\n", "Q5_Incident_Exposure\n", "============================================================\n" ] }, { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
FrequencyPercentage
Q5_Incident_Exposure
Yes6664.71
No2928.43
Not sure54.90
Missing21.96
\n", "
" ], "text/plain": [ " Frequency Percentage\n", "Q5_Incident_Exposure \n", "Yes 66 64.71\n", "No 29 28.43\n", "Not sure 5 4.90\n", "Missing 2 1.96" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "demographic_results = {}\n", "\n", "for col in demographic_columns:\n", "\n", " counts = (\n", " df[col]\n", " .fillna(\"Missing\")\n", " .value_counts()\n", " )\n", "\n", " percentages = (\n", " df[col]\n", " .fillna(\"Missing\")\n", " .value_counts(normalize=True)\n", " * 100\n", " )\n", "\n", " table = pd.DataFrame({\n", " \"Frequency\": counts,\n", " \"Percentage\": percentages.round(2)\n", " })\n", "\n", " demographic_results[col] = table\n", "\n", " print(\"\\n\" + \"=\" * 60)\n", " print(col)\n", " print(\"=\" * 60)\n", "\n", " display(table)" ] }, { "cell_type": "code", "execution_count": 22, "id": "7abe3a6e-05f5-4411-89ef-08d1d758d8f5", "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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", 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", 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Demographic visualisations\n", "demographic_titles = {\n", " \"Q1_Role\": \"Participant Current Role\",\n", " \"Q2_Experience\": \"Years of Professional Experience\",\n", " \"Q3_Organisation_Type\": \"Organisation Type\",\n", " \"Q4_Organisation_Size\": \"Organisation Size\",\n", " \"Q5_Incident_Exposure\": \"Cybersecurity Incident Exposure\"\n", "}\n", "\n", "\n", "for col in demographic_columns:\n", "\n", " plt.figure(figsize=(9, 5))\n", "\n", " order = (\n", " df[col]\n", " .fillna(\"Missing\")\n", " .value_counts()\n", " .index\n", " )\n", "\n", " sns.countplot(\n", " data=df,\n", " x=col,\n", " order=order\n", " )\n", "\n", " plt.title(demographic_titles[col])\n", " plt.xlabel(\"\")\n", " plt.ylabel(\"Number of Respondents\")\n", " plt.xticks(rotation=35, ha=\"right\")\n", " plt.tight_layout()\n", " plt.show()" ] }, { "cell_type": "markdown", "id": "78f649b1-467a-4b55-923e-fedeffe6065a", "metadata": {}, "source": [ "# Cronbach's Alpha function" ] }, { "cell_type": "code", "execution_count": 23, "id": "9f78cc52-6310-4123-9bb9-439711b29257", "metadata": {}, "outputs": [], "source": [ "def cronbach_alpha(data):\n", "\n", " \"\"\"\n", " Calculate Cronbach's alpha using complete cases\n", " for the supplied construct items.\n", " \"\"\"\n", "\n", " data = data.dropna()\n", "\n", " k = data.shape[1]\n", "\n", " if k < 2:\n", " return np.nan\n", "\n", " item_variances = data.var(axis=0, ddof=1)\n", " total_score_variance = data.sum(axis=1).var(ddof=1)\n", "\n", " if total_score_variance == 0:\n", " return np.nan\n", "\n", " alpha = (\n", " k / (k - 1)\n", " ) * (\n", " 1 -\n", " item_variances.sum() /\n", " total_score_variance\n", " )\n", "\n", " return alpha" ] }, { "cell_type": "markdown", "id": "cc9b524f-27f4-41de-9598-03189caa2fbf", "metadata": {}, "source": [ "# Reliability analysis" ] }, { "cell_type": "code", "execution_count": 24, "id": "0047fd1c-d715-4d0f-8060-28f9cb8eaf71", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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ConstructItemsComplete_CasesCronbach_Alpha
0OR51000.494
1TC5990.507
2EKS51020.586
3IRC51010.546
4DFR5960.567
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" ], "text/plain": [ " Construct Items Complete_Cases Cronbach_Alpha\n", "0 OR 5 100 0.494\n", "1 TC 5 99 0.507\n", "2 EKS 5 102 0.586\n", "3 IRC 5 101 0.546\n", "4 DFR 5 96 0.567" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "reliability_results = []\n", "\n", "for construct, items in construct_items.items():\n", "\n", " score_items = [\n", " f\"{item}_score\"\n", " for item in items\n", " ]\n", "\n", " complete_data = df[score_items].dropna()\n", "\n", " alpha = cronbach_alpha(\n", " complete_data\n", " )\n", "\n", " reliability_results.append({\n", " \"Construct\": construct,\n", " \"Items\": len(score_items),\n", " \"Complete_Cases\": len(complete_data),\n", " \"Cronbach_Alpha\": alpha\n", " })\n", "\n", "\n", "reliability_table = pd.DataFrame(\n", " reliability_results\n", ")\n", "\n", "display(\n", " reliability_table.round(3)\n", ")" ] }, { "cell_type": "code", "execution_count": 25, "id": "733a7139-7943-40c1-8ae9-7822cd4bc9b1", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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ConstructItemsComplete_CasesCronbach_AlphaInterpretation
0OR51000.494Poor
1TC5990.507Poor
2EKS51020.586Poor
3IRC51010.546Poor
4DFR5960.567Poor
\n", "
" ], "text/plain": [ " Construct Items Complete_Cases Cronbach_Alpha Interpretation\n", "0 OR 5 100 0.494 Poor\n", "1 TC 5 99 0.507 Poor\n", "2 EKS 5 102 0.586 Poor\n", "3 IRC 5 101 0.546 Poor\n", "4 DFR 5 96 0.567 Poor" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Reliability interpretation\n", "def interpret_alpha(alpha):\n", "\n", " if pd.isna(alpha):\n", " return \"Not available\"\n", "\n", " elif alpha >= 0.90:\n", " return \"Excellent\"\n", "\n", " elif alpha >= 0.80:\n", " return \"Good\"\n", "\n", " elif alpha >= 0.70:\n", " return \"Acceptable\"\n", "\n", " elif alpha >= 0.60:\n", " return \"Questionable\"\n", "\n", " else:\n", " return \"Poor\"\n", "\n", "\n", "reliability_table[\"Interpretation\"] = (\n", " reliability_table[\"Cronbach_Alpha\"]\n", " .apply(interpret_alpha)\n", ")\n", "\n", "display(reliability_table.round(3))" ] }, { "cell_type": "markdown", "id": "987d3ac9-9999-4dcc-a8f6-576252766d07", "metadata": {}, "source": [ "# Item-total correlations" ] }, { "cell_type": "code", "execution_count": 26, "id": "b84e3995-4b85-4bd6-bb8a-7601876b3ccd", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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ConstructItemCorrected_Item_Total_Correlation
0OROR10.239
1OROR20.223
2OROR30.386
3OROR40.225
4OROR50.272
5TCTC10.226
6TCTC20.350
7TCTC30.421
8TCTC40.237
9TCTC50.185
10EKSEKS10.416
11EKSEKS20.346
12EKSEKS30.375
13EKSEKS40.345
14EKSEKS50.243
15IRCIRC10.286
16IRCIRC20.267
17IRCIRC30.467
18IRCIRC40.293
19IRCIRC50.250
20DFRDFR10.287
21DFRDFR20.288
22DFRDFR30.283
23DFRDFR40.421
24DFRDFR50.364
\n", "
" ], "text/plain": [ " Construct Item Corrected_Item_Total_Correlation\n", "0 OR OR1 0.239\n", "1 OR OR2 0.223\n", "2 OR OR3 0.386\n", "3 OR OR4 0.225\n", "4 OR OR5 0.272\n", "5 TC TC1 0.226\n", "6 TC TC2 0.350\n", "7 TC TC3 0.421\n", "8 TC TC4 0.237\n", "9 TC TC5 0.185\n", "10 EKS EKS1 0.416\n", "11 EKS EKS2 0.346\n", "12 EKS EKS3 0.375\n", "13 EKS EKS4 0.345\n", "14 EKS EKS5 0.243\n", "15 IRC IRC1 0.286\n", "16 IRC IRC2 0.267\n", "17 IRC IRC3 0.467\n", "18 IRC IRC4 0.293\n", "19 IRC IRC5 0.250\n", "20 DFR DFR1 0.287\n", "21 DFR DFR2 0.288\n", "22 DFR DFR3 0.283\n", "23 DFR DFR4 0.421\n", "24 DFR DFR5 0.364" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "item_total_results = []\n", "\n", "for construct, items in construct_items.items():\n", "\n", " score_items = [\n", " f\"{item}_score\"\n", " for item in items\n", " ]\n", "\n", " for item in score_items:\n", "\n", " other_items = [\n", " x for x in score_items\n", " if x != item\n", " ]\n", "\n", " temp = df[\n", " [item] + other_items\n", " ].dropna()\n", "\n", " if len(temp) >= 3:\n", "\n", " total_without_item = (\n", " temp[other_items]\n", " .sum(axis=1)\n", " )\n", "\n", " correlation = (\n", " temp[item]\n", " .corr(total_without_item)\n", " )\n", "\n", " else:\n", "\n", " correlation = np.nan\n", "\n", " item_total_results.append({\n", " \"Construct\": construct,\n", " \"Item\": item.replace(\"_score\", \"\"),\n", " \"Corrected_Item_Total_Correlation\": correlation\n", " })\n", "\n", "\n", "item_total_table = pd.DataFrame(\n", " item_total_results\n", ")\n", "\n", "display(\n", " item_total_table.round(3)\n", ")" ] }, { "cell_type": "markdown", "id": "faf9024d-42bd-4913-b67a-3ccb0a3aefae", "metadata": {}, "source": [ "# Distribution and normality assessment" ] }, { "cell_type": "code", "execution_count": 27, "id": "ba2278a0-af19-423e-b39b-9bd61a0d9c2f", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
ConstructNMeanSDSkewnessKurtosis
0OR_Score1023.1350.7400.473-0.470
1TC_Score1023.3400.7630.657-0.480
2EKS_Score1023.2200.8220.1060.595
3IRC_Score1023.2080.8060.0690.001
4DFR_Score1023.2620.8240.287-0.102
\n", "
" ], "text/plain": [ " Construct N Mean SD Skewness Kurtosis\n", "0 OR_Score 102 3.135 0.740 0.473 -0.470\n", "1 TC_Score 102 3.340 0.763 0.657 -0.480\n", "2 EKS_Score 102 3.220 0.822 0.106 0.595\n", "3 IRC_Score 102 3.208 0.806 0.069 0.001\n", "4 DFR_Score 102 3.262 0.824 0.287 -0.102" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "distribution_results = []\n", "\n", "for col in construct_score_columns:\n", "\n", " values = df[col].dropna()\n", "\n", " distribution_results.append({\n", " \"Construct\": col,\n", " \"N\": len(values),\n", " \"Mean\": values.mean(),\n", " \"SD\": values.std(),\n", " \"Skewness\": stats.skew(values, bias=False),\n", " \"Kurtosis\": stats.kurtosis(\n", " values,\n", " fisher=True,\n", " bias=False\n", " )\n", " })\n", "\n", "\n", "distribution_table = pd.DataFrame(\n", " distribution_results\n", ")\n", "\n", "display(\n", " distribution_table.round(3)\n", ")" ] }, { "cell_type": "code", "execution_count": 28, "id": "c8acd3f5-1c9f-4c56-ae73-7b374da525f6", "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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", 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", 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", 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kBg8eLFq1aiVUKpWws7MTnTt3FosWLar2gILc3Fwxa9Ys4efnJ6ysrISHh4cYNWqUOHfunKlNTk6OeP7554VWqxVKpVL4+/uLefPmCZ1OV2VbAMSMGTNqrCs+Pl489dRTolWrVsLKykq4u7uLPn36iEWLFtXpfRFRw8iEuM1tx0REREREZoh9ZImIiIjIIrGPLBERmQWDwXDLsYllMtktn3hGRC0Pr8gSEZFZCAoKqjYW643T7UYQIKKWh1dkiYjILPzyyy/Vxva9kUajuYvVEJEl4M1eRERERGSR2LWAiIiIiCxSs+9aYDQakZqaCo1Gc0eDhBMRERFR0xNCoLCwEN7e3pDLb33NtdkH2dTUVPj6+kpdBhERERHVQ3JyMnx8fG7ZptkH2es3ByQnJ9fp8YdEREREJJ2CggL4+vrW6QbPZh9kr3cncHBwYJAlIiIishB16RJqNjd7RUZGQiaTYfbs2aZ5QggsWLAA3t7esLGxwcCBAxEbGytdkURERERkNswiyB49ehSff/45wsPDq8xfunQpli9fjo8++ghHjx6Fl5cXhg4disLCQokqJSIiIiJzIXmQLSoqwmOPPYYvvvgCzs7OpvlCCKxYsQJvvvkmxo8fj7CwMKxevRolJSVYu3athBUTERERkTmQPMjOmDEDo0aNwr333ltlfnx8PNLT0zFs2DDTPLVajQEDBuDAgQO1bk+v16OgoKDKRERERETNj6Q3e61btw7Hjx/H0aNHqy1LT08HAHh6elaZ7+npicTExFq3GRkZiYULFzZuoURERERkdiS7IpucnIxZs2bhm2++gbW1da3tbr5jTQhxy7vY5s2bh/z8fNOUnJzcaDUTERERkfmQ7IrssWPHkJmZiW7dupnmGQwG7N27Fx999BHOnz8PoPLKrFarNbXJzMysdpX2Rmq1Gmq1uukKJyIiIiKzINkV2SFDhuD06dOIiYkxTREREXjssccQExOD1q1bw8vLCzt27DCtU1ZWhj179qBPnz5SlU1EREREZkKyK7IajQZhYWFV5tnZ2cHV1dU0f/bs2Vi8eDGCg4MRHByMxYsXw9bWFpMmTZKiZCIiIiIyI2b9ZK9XX30VpaWlmD59OnJzc9GzZ09s3769To8sIyIiIqLmTSaEEFIX0ZQKCgrg6OiI/Px8PqKWiIiIyMzVJ7uZ9RVZIiK6taSkJGRnZ0tdRpNxc3ODn5+f1GUQkZlikCUislBJSUlo1749SktKpC6lydjY2uJcXBzDLBHViEGWiMhCZWdno7SkBI+9tgyefkFSl9PoMpIu49slryA7O5tBlohqxCBLRGThPP2C4BMcKnUZRER3nWTjyBIRERER3QkGWSIiIiKySAyyRERERGSRGGSJiIiIyCIxyBIRERGRRWKQJSIiIiKLxCBLRERERBaJQZaIiIiILBKDLBERERFZJAZZIiIiIrJIDLJEREREZJEYZImIiIjIIjHIEhEREZFFYpAlIiIiIovEIEtEREREFolBloiIiIgsEoMsEREREVkkBlkiIiIiskgMskRERERkkRhkiYiIiMgiMcgSERERkUVikCUiIiIiiyRpkF25ciXCw8Ph4OAABwcH9O7dG1u3bjUtnzp1KmQyWZWpV69eElZMREREROZCKeXOfXx88M4776BNmzYAgNWrV2PMmDE4ceIEQkNDAQDDhw9HVFSUaR2VSiVJrURERERkXiQNsqNHj67y+t///jdWrlyJQ4cOmYKsWq2Gl5eXFOURERERkRkzmz6yBoMB69atQ3FxMXr37m2av3v3bnh4eCAkJATPPPMMMjMzJaySiIiIiMyFpFdkAeD06dPo3bs3dDod7O3tsXHjRnTo0AEAMGLECDz88MPw9/dHfHw83nrrLQwePBjHjh2DWq2ucXt6vR56vd70uqCg4K68DyIiIiK6uyQPsm3btkVMTAzy8vLw008/YcqUKdizZw86dOiACRMmmNqFhYUhIiIC/v7+2LJlC8aPH1/j9iIjI7Fw4cK7VT4RERERSUTyrgUqlQpt2rRBREQEIiMj0alTJ7z//vs1ttVqtfD398fFixdr3d68efOQn59vmpKTk5uqdCIiIiKSkORXZG8mhKjSNeBGOTk5SE5OhlarrXV9tVpda7cDIiIiImo+JA2yb7zxBkaMGAFfX18UFhZi3bp12L17N7Zt24aioiIsWLAADz74ILRaLRISEvDGG2/Azc0N48aNk7JsIiIiIjIDkgbZjIwMTJ48GWlpaXB0dER4eDi2bduGoUOHorS0FKdPn8aaNWuQl5cHrVaLQYMG4fvvv4dGo5GybCIiIiIyA5IG2a+++qrWZTY2Nvjtt9/uYjVEREREZEkkv9mLiIiIiKghGGSJiIiIyCIxyBIRERGRRWKQJSIiIiKLxCBLRERERBaJQZaIiIiILBKDLBERERFZJAZZIiIiIrJIDLJEREREZJEYZImIiIjIIjHIEhEREZFFYpAlIiIiIovEIEtEREREFolBloiIiIgsEoMsEREREVkkBlkiIiIiskgMskRERERkkRhkiYiIiMgiMcgSERERkUVikCUiIiIii8QgS0REREQWiUGWiIiIiCwSgywRERERWSQGWSIiIiKySAyyRERERGSRGGSJiIiIyCIxyBIRERGRRZI0yK5cuRLh4eFwcHCAg4MDevfuja1bt5qWCyGwYMECeHt7w8bGBgMHDkRsbKyEFRMRERGRuZA0yPr4+OCdd95BdHQ0oqOjMXjwYIwZM8YUVpcuXYrly5fjo48+wtGjR+Hl5YWhQ4eisLBQyrKJiIiIyAxIGmRHjx6NkSNHIiQkBCEhIfj3v/8Ne3t7HDp0CEIIrFixAm+++SbGjx+PsLAwrF69GiUlJVi7dq2UZRMRERGRGTCbPrIGgwHr1q1DcXExevfujfj4eKSnp2PYsGGmNmq1GgMGDMCBAwdq3Y5er0dBQUGViYiIiIiaH8mD7OnTp2Fvbw+1Wo3nn38eGzduRIcOHZCeng4A8PT0rNLe09PTtKwmkZGRcHR0NE2+vr5NWj8RERERSUPyINu2bVvExMTg0KFD+Mc//oEpU6bg7NmzpuUymaxKeyFEtXk3mjdvHvLz801TcnJyk9VORERERNJRSl2ASqVCmzZtAAARERE4evQo3n//fbz22msAgPT0dGi1WlP7zMzMaldpb6RWq6FWq5u2aCIiIiKSnORXZG8mhIBer0dgYCC8vLywY8cO07KysjLs2bMHffr0kbBCIiIiIjIHkl6RfeONNzBixAj4+vqisLAQ69atw+7du7Ft2zbIZDLMnj0bixcvRnBwMIKDg7F48WLY2tpi0qRJUpZNRERERGZA0iCbkZGByZMnIy0tDY6OjggPD8e2bdswdOhQAMCrr76K0tJSTJ8+Hbm5uejZsye2b98OjUYjZdlEREREZAYkDbJfffXVLZfLZDIsWLAACxYsuDsFEREREZHFMLs+skREREREdcEgS0REREQWiUGWiIiIiCwSgywRERERWSQGWSIiIiKySAyyRERERGSRGGSJiIiIyCIxyBIRERGRRWKQJSIiIiKLxCBLRERERBaJQZaIiIiILBKDLBERERFZJAZZIiIiIrJIDLJEREREZJEYZImIiIjIIjHIEhEREZFFYpAlIiIiIovEIEtEREREFolBloiIiIgsEoMsEREREVkkBlkiIiIiskgMskRERERkkRhkiYiIiMgiMcgSERERkUVikCUiIiIii8QgS0REREQWSdIgGxkZie7du0Oj0cDDwwNjx47F+fPnq7SZOnUqZDJZlalXr14SVUxERERE5kLSILtnzx7MmDEDhw4dwo4dO1BRUYFhw4ahuLi4Srvhw4cjLS3NNP36668SVUxERERE5kIp5c63bdtW5XVUVBQ8PDxw7Ngx3HPPPab5arUaXl5ed7s8IiIiIjJjZtVHNj8/HwDg4uJSZf7u3bvh4eGBkJAQPPPMM8jMzJSiPCIiIiIyI5Jekb2REAJz5sxBv379EBYWZpo/YsQIPPzww/D390d8fDzeeustDB48GMeOHYNara62Hb1eD71eb3pdUFBwV+onIiIiorurQUE2Pj4egYGBjVrIzJkzcerUKezfv7/K/AkTJpi+DwsLQ0REBPz9/bFlyxaMHz++2nYiIyOxcOHCRq2NiIiIiMxPg7oWtGnTBoMGDcI333wDnU53x0W88MIL2Lx5M3bt2gUfH59bttVqtfD398fFixdrXD5v3jzk5+ebpuTk5Duuj4iIiIjMT4OC7MmTJ9GlSxe8/PLL8PLywnPPPYcjR47UeztCCMycORMbNmzAzp0763SVNycnB8nJydBqtTUuV6vVcHBwqDIRERERUfPToCAbFhaG5cuXIyUlBVFRUUhPT0e/fv0QGhqK5cuXIysrq07bmTFjBr755husXbsWGo0G6enpSE9PR2lpKQCgqKgIc+fOxcGDB5GQkIDdu3dj9OjRcHNzw7hx4xpSOhERERE1E3c0aoFSqcS4ceOwfv16LFmyBJcvX8bcuXPh4+ODJ554Amlpabdcf+XKlcjPz8fAgQOh1WpN0/fffw8AUCgUOH36NMaMGYOQkBBMmTIFISEhOHjwIDQazZ2UTkREREQW7o5GLYiOjsbXX3+NdevWwc7ODnPnzsW0adOQmpqKt99+G2PGjLlllwMhxC23b2Njg99+++1OSiQiIiKiZqpBQXb58uWIiorC+fPnMXLkSKxZswYjR46EXF55gTcwMBCfffYZ2rVr16jFEhERERFd16Agu3LlSjz11FN48skna33ilp+fH7766qs7Ko6IiIiIqDYNCrK1DX11I5VKhSlTpjRk80REREREt9Wgm72ioqLwww8/VJv/ww8/YPXq1XdcFBERERHR7TQoyL7zzjtwc3OrNt/DwwOLFy++46KIiIiIiG6nQUE2MTGxxocX+Pv7Iykp6Y6LIiIiIiK6nQYFWQ8PD5w6dara/JMnT8LV1fWOiyIiIiIiup0G3ew1ceJEvPjii9BoNLjnnnsAAHv27MGsWbMwceLERi2QiIgq5ZeU41jSNRxNyMWlzCJcTsuBz8xvsCnZCvKUS5BBBhuVAhprJRysreDpoEYrJxu42Kkgk8mkLp+IqNE1KMguWrQIiYmJGDJkCJTKyk0YjUY88cQT7CNLRNSIMgt0+N+pNPxyKhUnkvKqLVfYOcEgAINBABAoKzUiv7QcQCnO/vVwRRsrBYI87NDeywFaR2uGWiJqNhoUZFUqFb7//nv861//wsmTJ2FjY4OOHTvC39+/sesjImqRjiVew2d7ruD3uAwYb3gIYms3O0QEOKNjK0eU5qRi5lOP48n/ew9e/sEQAEr0BhToypFXUo7U/FKk5+tQWm7AmZQCnEkpgKONFbr4OiHU2wFKxR09pZyISHJ39IjakJAQhISENFYtREQt3sHLOXhv+3lEJ+aa5nXxc8IDnbwxqqMWHg7WpvnHj19DeVY87JWAk60KAOBsC7SCjamNwShwNbcE59MLcSmrCPml5dh9IQuH46+hq78TOvs4MdASkcVqUJA1GAxYtWoV/vjjD2RmZsJoNFZZvnPnzkYpjoiopYjPLkbkr3HYfjYDAKBSyDG2izee6d8awZ6aBm9XIZfB39UO/q52GGQw4mxaAY4l5qJQV4E/L+Xg9NV83BPijtZuduxyQEQWp0FBdtasWVi1ahVGjRqFsLAw/vIjImqgcoMRK3dfxoc7L6LcIKCQyzCphx9mDm4DzxuuvjYGK4UcnXycEObtiPMZhTh4OQcFugr871Qa/F1tMaSdBzTWVo26TyKiptSgILtu3TqsX78eI0eObOx6iIhajNjUfLzywymcTSsAAAwIccf/jWp/R1dg60Ihl6GD1gHBHvY4mnANxxPzkJhTgm8OJ2FQW3e09dTwAgURWYQG3+zVpk2bxq6FiKhFEEJg1YEELP41DuUGASdbKyx8IBQPdPK+qwHSSiFHnyA3tPdywG9n05FRoMdvsRmIzy7GkHaeUCnZd5aIzFuDfku9/PLLeP/99yGEuH1jIiIyKdCVY/q3x7Hwl7MoNwgM7eCJHS8NwJjOrSS7Cupsp8Ij3XzRq7UL5DLgQkYR1kcnI7ekTJJ6iIjqqkFXZPfv349du3Zh69atCA0NhZVV1T5VGzZsaJTiiIiak8tZRXh6dTTis4thpZDhjZHtMbVPgFl8jC+Xy9Az0BW+zrbYcjoNOcVlWHckGcPDvBDoZid1eURENWpQkHVycsK4ceMauxYiombrwKVsPP/NMRToKtDKyQYfTeqCLn7OUpdVjbeTDSb18MOW02lIy9fhl5OpGNTWAx19HKUujYiomgYF2aioqMaug4io2fr+aBLe3HgGFUaBLn5O+HxyBNw1aqnLqpWdWokHu/pg57lMnE0rwM7zmSjUl6N3a1ezuHpMRHRdg3vyV1RU4Pfff8dnn32GwsJCAEBqaiqKiooarTgiIksmhMDHuy7htZ9Oo8Io8EAnb3z3TC+zDrHXKeQy3NveAz0DXQAARxNy8XtcJoy8N4KIzEiDrsgmJiZi+PDhSEpKgl6vx9ChQ6HRaLB06VLodDp8+umnjV0nEZFFMRoFFv8ahy/3xwMApg8Mwiv3tbWoK5oymQy9WrtCY63EH3GVV2cNRoFhHTwhl1vO+yCi5qtBV2RnzZqFiIgI5Obmwsbm70chjhs3Dn/88UejFUdEZImMRoF5G06bQuz/jWqPV4e3s6gQe6NQb0eMCPOCXAaczyjE1jPpMBh5ZZaIpNfgUQv+/PNPqFSqKvP9/f2RkpLSKIUREVkig1HgtZ9O4cdjVyGXAUsf6oSHuvlIXdYdC/bUQCGX4dfT6biUVYRtZ9Irwy2vzBKRhBp0RdZoNMJgMFSbf/XqVWg0TftEGiIic2UwCrzy40n8eOwqFHIZ3p/YpVmE2Otau9vj/k5aKGQyXMoqwva4DPaZJSJJNSjIDh06FCtWrDC9lslkKCoqwvz58/nYWiJqkYQQmLfhFDYcT4FCLsMHE7tgdCdvqctqdAGudhjZ8a9uBumF2Hkukw/HISLJNCjI/uc//8GePXvQoUMH6HQ6TJo0CQEBAUhJScGSJUsau0YiIrMmhEDk1nNYH13ZneCDiV0wKlwrdVlNprW7Pe4L9YIMQGxqAQ5eyZG6JCJqoRrUR9bb2xsxMTH47rvvcPz4cRiNRkybNg2PPfZYlZu/iIhagpV7LuPzvVcAAO88GN6sQ+x1IZ4alBuM+D0uE0cTcqGxtkLHVnxoAhHdXQ0eR9bGxgZPPfUUPvroI3zyySd4+umn6x1iIyMj0b17d2g0Gnh4eGDs2LE4f/58lTZCCCxYsADe3t6wsbHBwIEDERsb29CyiYga1drDSVi6rfL31psj2+ORCF+JK7p7Qr0dTePM7jqXiSvZHEeciO6uBl2RXbNmzS2XP/HEE3Xazp49ezBjxgx0794dFRUVePPNNzFs2DCcPXsWdnaVz/ZeunQpli9fjlWrViEkJASLFi3C0KFDcf78ed5YRkSS2nIqDW9uOg2gcpzYZ+5pLXFFd1/PQBcU6ipwNq0AW0+n48FuPvBysJa6LCJqIRoUZGfNmlXldXl5OUpKSqBSqWBra1vnILtt27Yqr6OiouDh4YFjx47hnnvugRACK1aswJtvvonx48cDAFavXg1PT0+sXbsWzz33XEPKJyK6Y3svZGH29ycgBDCppx9eua+t1CVJQiaTYXA7DxTrK5B4rQSbY1IxobsvHG2spC6NiFqABnUtyM3NrTIVFRXh/Pnz6NevH7777rsGF5Ofnw8AcHGp/KgqPj4e6enpGDZsmKmNWq3GgAEDcODAgRq3odfrUVBQUGUiImpMp67m4bn/HkO5QWBUuBb/GhNmsQ87aAwKuQwjO2rhbq9GabkBm2JSUFpefYhGIqLG1uA+sjcLDg7GO++8U+1qbV0JITBnzhz069cPYWFhAID09HQAgKenZ5W2np6epmU3i4yMhKOjo2ny9W05/dWIqOml5JVi2upolJYb0D/YDf95pDMUfCgAVEo5HujsDY21Enkl5fjlZCoqjEapyyKiZq7RgiwAKBQKpKamNmjdmTNn4tSpUzVe0b35SocQotarH/PmzUN+fr5pSk5OblA9REQ3K9SV46moo8gq1KOdlwafPNYVKmWj/hq1aPZqJcZ08oZKKUdavg67z2dxjFkialIN6iO7efPmKq+FEEhLS8NHH32Evn371nt7L7zwAjZv3oy9e/fCx+fvp+B4eXkBqLwyq9X+PZxNZmZmtau016nVaqjV6nrXQER0KxUGI2asPYHzGYVw16jx1dTu0FizH+jNXO3VGBHmhc0xqYhNLYC7Ro1OPk5Sl0VEzVSDguzYsWOrvJbJZHB3d8fgwYPx3nvv1Xk7Qgi88MIL2LhxI3bv3o3AwMAqywMDA+Hl5YUdO3agS5cuAICysjLs2bOHD14gortGCIH5m2Ox90IWbKwU+HpKd7Ry4pjZtQlwtUPfNm7Yfykbey9kwdVOBR9nW6nLIqJmqEFB1thI/Z5mzJiBtWvX4ueff4ZGozH1e3V0dISNjQ1kMhlmz56NxYsXIzg4GMHBwVi8eDFsbW0xadKkRqmBiOh2vtofj28PJ0EmA96f2BkdfTjw/+109XNCVqEe5zMK8evpdEzs7gsHjmRARI2sQUG2saxcuRIAMHDgwCrzo6KiMHXqVADAq6++itLSUkyfPh25ubno2bMntm/fzjFkieiu+C02Hf/+NQ5A5QMPhoV6SVyRZZDJZLi3vQdyS8qQWajHL6dS8UiEL6wU7FNMRI2nQUF2zpw5dW67fPnyWpfV5SYAmUyGBQsWYMGCBXXeJxFRYzibWoDZ62IgBPB4Lz9M6xd4+5XIRKmQY1S4FuuOJCO7qAw7zmZgRJhXix6qjIgaV4OC7IkTJ3D8+HFUVFSgbdvKQcAvXLgAhUKBrl27mtrxlxURWaqcIj2eWfP3MFsLRofyd1oDOFhbYVS4FhuOX8XFzCK4J+aie4CL1GURUTPRoCA7evRoaDQarF69Gs7OzgAqH5Lw5JNPon///nj55ZcbtUgiorup3GDE9G+PIyWvFAGutvjo0a5Q8iPxBmvlZIOBIR7YeT4TBy/nwNPBGn4uvPmLiO5cg34zv/fee4iMjDSFWABwdnbGokWL6jVqARGROfrX/87icPw12KkU+OKJCDja8ialOxXWygEdtA4QALadSUeRrkLqkoioGWhQkC0oKEBGRka1+ZmZmSgsLLzjooiIpPLdkSSsOZgImQxYMbELgj15Y2ljkMlkGNTWHW72KpSWG/DrmTQYjHxYAhHdmQYF2XHjxuHJJ5/Ejz/+iKtXr+Lq1av48ccfMW3aNIwfP76xayQiuiuOJlzD2z+fAQC8PDQEQzvU/OAVahilQo5RHbWmJ3/tv5QtdUlEZOEa1Ef2008/xdy5c/H444+jvLy8ckNKJaZNm4Zly5Y1aoFERHdDal4p/vHNMZQbBEZ11GLGoDZSl9QsOdmqcF8HT/xyKg0xyXnQOlojhFe9iaiBGhRkbW1t8cknn2DZsmW4fPkyhBBo06YN7OzsGrs+IqImV1pmwLP/jUZ2URnaax2w7OFwjlDQhFq72yPC3xnRibn4PS4DbvZquNippC6LiCzQHd2Gm5aWhrS0NISEhMDOzq5O48ISEZkTIQRe++kUzqQUwMVOhc8nd4OtStJnxbQIvVu7wsfZBuUGgS2n0lBW0ThPjCSilqVBQTYnJwdDhgxBSEgIRo4cibS0NADA008/zaG3iMiifLb3CjafTIVSLsMnj3WFL4eFuivkchmGh3rBTq3AtZIy/HEugxdDiKjeGhRkX3rpJVhZWSEpKQm2tn//0p8wYQK2bdvWaMURETWlXecysWTbOQDA/NEd0Ku1q8QVtSx2aiVGhmkhlwEXMopw8mq+1CURkYVpUJDdvn07lixZAh8fnyrzg4ODkZiY2CiFERE1pctZRXhx3QkIATzaww+P9/KXuqQWydvJBv3auAEA9l3MQlp+qcQVEZElaVCQLS4urnIl9rrs7Gyo1eo7LoqIqCnll5bjmdXRKNRVoHuAMxY+wMfPSqmzrxOCPexhFMCvp9NRUsaHJRBR3TQoyN5zzz1Ys2aN6bVMJoPRaMSyZcswaNCgRiuOiKixGYwCs9edwJXsYng7WuOTx7pBpeTjZ6Ukk8lwb3tPONtaoUhfgW1n0mFkf1kiqoMG3Zq7bNkyDBw4ENHR0SgrK8Orr76K2NhYXLt2DX/++Wdj10hE1GiW/XYeu85nQa2U4/MnIuCu4adI5kClrHxYwvfRyUjOLcWhKznwk7ooIjJ7DboM0aFDB5w6dQo9evTA0KFDUVxcjPHjx+PEiRMICgpq7BqJiBrFzzEp+HTPZQDA0ofCEdbKUeKK6Eau9moMaVf5NLWjCblIK2V3DyK6tXpfkS0vL8ewYcPw2WefYeHChU1RExFRozt1NQ+v/ngKAPCPgUEY07mVxBVRTdp6aZCWX4qTV/NxNFsJpSMfE0xEtav3FVkrKyucOXOGN0YQkcXILNDh2TXHoK8wYnA7D8wd1lbqkugW+ge7w8vBGuVCBrex81BmYH9ZIqpZg7oWPPHEE/jqq68auxYiokanrzDg+W+OIb1AhzYe9nh/Ymco5PyPuDlTyGUY2dELKrmA2qsNvjzO8WWJqGYNutmrrKwMX375JXbs2IGIiAjY2dlVWb58+fJGKY6I6E4IIfB/G8/geFIeHKyV+OKJCGisraQui+pAY22FHm4V2JehwO/xpVh/NBmPdPeVuiwiMjP1CrJXrlxBQEAAzpw5g65duwIALly4UKUNuxwQkbmI+jMBPxy7CrkM+GhSVwS62d1+JTIbntYC+fu+hdM9k/HWz2fQwduBN+gRURX1CrLBwcFIS0vDrl27AFQ+kvaDDz6Apyc74xORedl3MQuLtpwFALwxsj3uCXGXuCJqiPyD6zF4wtM4nqbH9G+P45cX+sHRhlfViahSvfrIipsGqN66dSuKi4sbtSAiojuVkF2MmWtPwCiAB7v6YFq/QKlLogYTmNXDCT7ONki6VoKX18fAaOTNX0RU6Y4eZ3NzsCUiklqhrhxPr4lGfmk5Ovs64d/jwtjlycJp1HKsfKwbVAo5fo/LxMq/xgImIqpXkJXJZNX+IPAPBBGZi8rHz8bgUmYRPB3U+HxyN1hbKaQuixpBRx9HLBwTCgB4d/t57DqfKXFFRGQO6tVHVgiBqVOnQq2ufKSjTqfD888/X23Ugg0bNjRehUREdbT41zj8cS6z8vGzkyPg4WAtdUnUiCZ298Wpq3n47kgyXvzuBH6e0Ret3e2lLouIJFSvIDtlypQqrx9//PFGLYaIqKG+PZyIr/bHAwDee6QTOvk6SVsQNTqZTIYFD4TiQkYRjiXm4tn/HsPG6X04pBpRC1avIBsVFdWoO9+7dy+WLVuGY8eOIS0tDRs3bsTYsWNNy6dOnYrVq1dXWadnz544dOhQo9ZBRJZt38UsvP1zLADg5aEhuD/cW+KKqKmolQqsfKwrRn+0H5cyizBn/Ul89ng3yPmQC6IW6Y5u9rpTxcXF6NSpEz766KNa2wwfPhxpaWmm6ddff72LFRKRubuYUYjp3xyHwSgwvksrzBzcRuqSqIl5OFjjs8kRUCnl2HE2A+//cVHqkohIIg16sldjGTFiBEaMGHHLNmq1Gl5eXnepIiKyJDlFejy1+igK9RXoEeCCyAc78gbUFqKzrxP+PTYMr/x4Cu//cREdvB1wXyj/VhC1NJJeka2L3bt3w8PDAyEhIXjmmWeQmXnrO1X1ej0KCgqqTETU/OjKDXj2v8eQfK0U/q62+HRyN6iVHKGgJXk4whdT+wQAAOZ8H4Pz6YXSFkREd51ZB9kRI0bg22+/xc6dO/Hee+/h6NGjGDx4MPR6fa3rREZGwtHR0TT5+vLZ3ETNjdEoMPeHkziWmAsHayW+mtIdLnYqqcsiCbw5qj16t3ZFcZkBT606iqzC2v8+EFHzY9ZBdsKECRg1ahTCwsIwevRobN26FRcuXMCWLVtqXWfevHnIz883TcnJyXexYiK6Gxb/Gof/nUqDlUKGTx/vhjYeHIKppbJSyPHJY10R6GaHlLxSPL0mGqVlBqnLIqK7xKyD7M20Wi38/f1x8WLtHfvVajUcHByqTETUfHy57wq+/GuYrWUPdUKfNm4SV0RSc7ZT4eup3eFka4WTyXl46Xs+xpaopbCoIJuTk4Pk5GRotVqpSyEiCfzvVCoWbYkDALw+oh3GdmklcUVkLgLd7PD55AioFHJsi03Hkm3npC6JiO4CSYNsUVERYmJiEBMTAwCIj49HTEwMkpKSUFRUhLlz5+LgwYNISEjA7t27MXr0aLi5uWHcuHFSlk1EEjh0JQdzvj8JAJjS2x/P3dNa4orI3PQIdMGyh8MBAJ/tvYK1h5MkroiImpqkQTY6OhpdunRBly5dAABz5sxBly5d8Pbbb0OhUOD06dMYM2YMQkJCMGXKFISEhODgwYPQaDRSlk1Ed9n59EI8syYaZQYjhod64e3RoRxmi2o0pnMrvHRvCADgrZ/PYO+FLIkrIqKmJOk4sgMHDoQQtfdj+u233+5iNURkjlLzSjE16ggKdRWI8HfGiomdoeBTnOgWXhzSBok5xdhwIgXTvz2Odc/2QlgrR6nLIqImIGmQJSK6lewiPR7/8jDS8nUIcrfDl1MiYG1V97Fik5KSkJ2d3YQVSisuLk7qEsySTCZD5IMdkZpfikNXrmHK10ew/vneCHLn6BZEzQ2DLBGZpfzScjzx1RFcyS5GKycb/HdaTzjZ1n2s2KSkJLRr3x6lJSVNWKV5KCoqkroEs6NWKvDFExGY9MVhnE7Jx+QvD+OHf/RBKycbqUsjokbEIEtEZqekrALTVh3F2bQCuNmr8c3TPeFdzwCSnZ2N0pISPPbaMnj6BTVRpdKKO7IHW1e/D51OJ3UpZkljbYXVT/XAw58ewOWsYkz+8jDWP98bbvZqqUsjokbCIEtEZkVfYcBz/z2G6L+e2vXfaT0Q6GbX4O15+gXBJzi0ESs0HxlJl6Uuwey52KnwzdM98dDKg7iSXYwnvjqC757tBUcbK6lLI6JGYFHjyBJR81ZhMGL2uhjsu5gNGysFop7sgfZaPtSE7ozW0QbfPN0TbvZqnE0rwNOrj/LpX0TNBIMsEZkFo1Fg3obT2HomHSqFHJ8/0Q3d/J2lLouaiUA3O6x5qgccrJU4mpCLZ/8bDV05wyyRpWOQJSLJXQ+xPxy7CrkM+ODRLugf7C51WdTMdPB2QNST3WFjpcC+i9l4Zg3DLJGlYx9ZohbKXIamMgqBT6Pz8Xt8KeQyYFZPJ3iUpeL48dQ72i6HpqKadPN3waonu+PJVUex72I2nl4djS+eiICNqu7DuhGR+WCQJWqBzGdoKhlc7psOTecREEYDMv63HLPf2dOoe+DQVHSznq1dsfqpHpj69RHsv5SNKVFH8NWUCGiseQMYkaVhkCVqgcxhaCohgBO5CsQXKQAI9HAX8Js5C8CsRtk+h6aiW+ke4ILVT/XAk1FHcST+GiZ9cRirn+oBF7u6j1VMRNJjkCVqwaQamkoIgV3nsxBflA8ZgGEdvNCukUcn4NBUdDsRAS747tleeOLrIzidko9HPjuI/07rAa0jH5pAZCl4sxcR3VVGIbDzXCZOp+QDAIZ28Gz0EEtUV2GtHLH+ud7QOlrjUmYRxn18AOfSC6Qui4jqiEGWiO4ag1Fge2wGzqRWBoWhHTw5TixJro2HPX54vjfaeNgjvUCHh1cexJ+XpL8Rkohuj0GWiO6KCoMRv55Ow/mMQshlwIgwL3RgiCUz4eNsi5+e74MegS4o1FdgatQRfH80SeqyiOg2GGSJqMmVG4zYfCoVV7KLoZDLcH+4N0I8NVKXRVSFo60V1jzVA/eHa1FuEHjtp9NY+EssKgxGqUsjolrwZi8ialL6cgN+PpmKtHwdrBQyjA73hq+LrdRlEdXI2kqBDyZ2QRsPe6z4/SKi/kzApcwivD+xC0c0oFqZy7jcTcnNzQ1+fn5Sl1ENgywRNZmSsgpsiklFVqEeaqUcYzu3gpejtdRlEd2SXC7D7HtD0NZTgznrT2LfxWzc/8E+fPxYV3Tx42OTqSrzGZe7adnY2uJcXJzZhVkGWSJqEnklZdgUk4r80nLYWCkwrksruGvUUpdFVGcjOmoR4GaH6d8eR3x2MR757CDeHNkeU/oEQCaTSV0emQlzGJe7qWUkXca3S15BdnY2gywRNX8ZBTr8HJOK0nIDHKyVGNulFZxt+bEsWZ72Wgf8PLMvXvvxFLaeSceCX85i78VsLH0oHG72/I8Z/U2qcblbOt7sRUSNKiGnGD8dv4rScgPcNWo8EuHLEEsWzcHaCp881hXzR3eASinHznOZGL5iL3aey5C6NKIWj0GWiBrN2bQC/HIyFeUGAT8XWzzU1Qd2an7wQ5ZPJpPhyb6B2DyzL9p6apBdVIanVkVjzvoY5JWUSV0eUYvFIEtEd0wIgaMJ17DjbAaMAmjrpcEDnbyhUvJXDDUv7bwquxo83S8QMhmw4XgK7l2+F1tOpUEIIXV5RC0O/8oQ0R0xGAX+OJeJA5dzAADd/JxxXwdPKOS8GYaaJ2srBf7v/g746R99EORuh+wiPWasPY4nvj6CK1lFUpdH1KIwyBJRg+nKDdgUk4LY1ALIAAwIcUe/YDfe0U0tQlc/Z2x5sT9eHBIMlVKOfRezMXzFPkRujUN+abnU5RG1CAyyRNQgeSVlWB+djKu5pZUPOujkjc6+TlKXRXRXWVspMGdoCLbPvgcDQtxRZjDisz1XMHDZLqw+kAB9hUHqEomaNQZZIqq3lLxSfB+djNySctirlXi4my8C3eykLotIMgFudlj1ZHd8NSUCbTzskVtSjvmbYzFw2W6sOZgAXTkDLVFTkDTI7t27F6NHj4a3tzdkMhk2bdpUZbkQAgsWLIC3tzdsbGwwcOBAxMbGSlMsEQEA4tIKsPF4CnTlRnho1JjY3ZcPOiBC5cgGQ9p7Ytus/vjX2DB4OqiRlq/D2z/H4p6lu/DV/niUljHQEjUmSYNscXExOnXqhI8++qjG5UuXLsXy5cvx0Ucf4ejRo/Dy8sLQoUNRWFh4lyslIqNRYO/FLGw/mwGDEAhyt8ND3Ti8FtHNlAo5Jvfyx55XBuFfY0Lh7WiNzEI9/vW/s+i/dCc+2X0J14o5ZBdRY5D0L9CIESMwYsSIGpcJIbBixQq8+eabGD9+PABg9erV8PT0xNq1a/Hcc8/dzVKJWjRduQFbz6Qj6Vrls8S7Bzijd2tX3tRFdAvWVgpM7h2ACd39sOH4VXy8+xKSr5Vi6bbzWPH7RYzqqMXjvfzR1c+J/5aIGshs+8jGx8cjPT0dw4YNM81Tq9UYMGAADhw4IGFlRC1LdpEe644mI+laCZRyGUaGeaFPEEcmIKorlVKOiT38sPPlgXjv4U7o2MoRZRVGbDyRggdXHsDID/bj28OJKNJXSF0qkcUx288E09PTAQCenp5V5nt6eiIxMbHW9fR6PfR6vel1QUFB0xRI1AJcyizC9rPpKDcIOFgrcX+4N/vDEjWQlUKOB7v54MFuPjiZnIdvDiVi88lUxKUV4M2NZ/Cv/53FkPaeGNPJGwPaukOtVEhdMpHZM9sge93NV32EELe8EhQZGYmFCxc2dVlEzZoQAofjr+Fw/DUAgI+zDUaGaWGj4h9WosbQydcJnXyd8Oao9vjx2FWsPZyEK9nF2HIqDVtOpcHBWokRYVo80NkbPQNdoFSY7QeoRJIy2yDr5eUFoPLKrFarNc3PzMysdpX2RvPmzcOcOXNMrwsKCuDr69t0hRI1M2UVRmw/m47LWcUAgM6+Tujfxg1yPqmLqNE52arwdP/WmNYvEGdSCvBzTAp+OZWKjAI9vo9OxvfRyXC0scLgdh64t70n7glxg8baSuqyicyG2QbZwMBAeHl5YceOHejSpQsAoKysDHv27MGSJUtqXU+tVkOt5kefRA2RW1KGLafSkFNcBoVMhsHtPNDB20HqsoiaPZlMho4+jujo44h5I9vjSPw1bD6Zim1n0pBbUo6NJ1Kw8UQKrBQy9GrtisHtPNA/2A1B7vbsr04tmqRBtqioCJcuXTK9jo+PR0xMDFxcXODn54fZs2dj8eLFCA4ORnBwMBYvXgxbW1tMmjRJwqqJmqdLmUXYcTYDZQYj7FQK3B/uDS9Ha6nLImpxFHIZege5oneQKxaNDcPxpFz8fjYDO+IycCWrGPsuZmPfxWwAgKeDGn3buKFfGzf0beMGTwf+m6WWRdIgGx0djUGDBpleX+8SMGXKFKxatQqvvvoqSktLMX36dOTm5qJnz57Yvn07NBqNVCUTNTtGo8CBKzk4lpgLAPB2ssbIMC3HhyUyAwq5DN0DXNA9wAXzRrbH5awi/BGXgb0XsnEk4RoyCvTYcDwFG46nAACCPexNwbZ7oAscbdgNgZo3Sf9SDRw4EEKIWpfLZDIsWLAACxYsuHtFEbUgOgOw8UQKruaVAgC6+Dmhb5AbFOwPS2SWgtztEeRuj2fvCYKu3IBjibnYfykbf17KxumUfFzMLMLFzCKsOpAAmQxo5+WAnoGVQbh7oDM8NLxiS80LL7kQtVDqVu3wR7oVdIZSWClkGNreE8Ge/LSDyFJYWynQ968uBQCQV1KGg5dzTME2IacEcWkFiEsrwKoDCQCAAFdb9Pgr2PYIdIGfiy372JJFY5AlamGEENhyoRiej74DnUEGF1sVRoVr4WKnkro0IroDTrYqjOioxYiOlSP9ZBbocCThGo7+NZTe+YxCJOSUICGnBOujrwIAPDRq9Ah0MYXbtp4ajlBCFoVBlqgFKdZXYN6G09h8sgAyhRI+tgaM7u4LlZJjVBI1Nx4O1rg/3Bv3h3sDAPJLynEs6RqOxOfiSHwOTqfkI7NQj/+dSsP/TqUBAByslYgIcEE3f2d083dGJx8njh9NZo1BlqiFuJBRiOnfHselzCIoZEDW759j/NSpDLFELYSjrRUGt/PE4HaVY7GXlhkQk5yHI/HXcDThGo4n5aJAV4Gd5zKx81wmAEAplyHU2wHd/F0QEVAZbjkyApkTBlmiFuCH6GS89fMZ6MqN8NCoMSvCHo+/sxmyJ6dKXRoRScRGpTAN8wUA5QYjYlMLcCwxF8cSryE6IReZhXqcvJqPk1fz8fWf8QAqn/TXzd8ZEf7O6ObvgrZeGt4gSpJhkCVqxkrKKvDWplj8dLyyP1z/YDf8Z0JnJF2IlbgyIjI3Vgo5Ovs6obOvE6b1C4QQAldzS/8KtrmITszF+fQCXM0txdXcUvwckwoAsFcr0cXPCV39nBER4Iwufs6w5/B9dJfwTCNqpi7+1ZXgYmYR5DJgztAQTB/YBnK5DElSF0dEZk8mk8HXxRa+LrYY26UVAKBQV46Y5DxEJ+TieFIuTiTloUhfUeUhDXIZ0NbL4a8rtpWTj7MNR0egJsEgS9QM/XTsKv5v0xmUlhvgrlHjg4ldTB8fEhE1lMbaCv2D3dE/2B0AYDAKnEsvwPG/rtgeS8zF1dxS07Bf/z2UCKDyCWTd/J3R2dcJ4T5OCGvlyKu21Ch4FhE1I6VlBszffMY0tE6/NpVdCdw1aokrI6LaJCUlITs7W+oy7kioGggNAaaEOOFaqQbnsstwLrsc53LKEJ9XjowCPX49nY5fT6cDAGSyyoc7hPs4IryVI8J9ndBB6wBrK46QQPXDIEvUTFzKrOxKcCGjsivB7HtDMGNQG96EQWTGkpKS0K59e5SWlEhdSpOxcXDCum1/IlmnwqmreTh9NR+p+TpcyizCpcwi0+N1lXIZgj01aO+lQTutBm29HNDeSwN3jZrdEqhWDLJEzcCG41fx5sbKrgRu9mp88Ghn9Alyk7osIrqN7OxslJaU4LHXlsHTL0jqchpdRtJlfLvkFfiodXigdwfT/MxCHU5fzcepq/k4dTUPp67mI6e4zNQlASf+3oazrRXaeTmgrZcG7bw0aONhjwA3O7jaqRhwiUGWyJKVlFVg4eaz+D46GQDQt40r/jOhM5+nTmRhPP2C4BMcKnUZd42HxhpD2ltjSPvKMW2FEEjN1yE2JR/n0wtxLr0Q59ILEJ9djNySchy8koODV3KqbEOjViLAzQ4BbnYIdLVFgJsd/F3tEOBqCxeG3BaDQZbIQp1NLcAL3x3H5axiyGTA7CEhmDmYXQmIyPLIZDK0crJBKycbDAv1Ms3XlRtwKbOoMtimFeB8RiGuZBUjNb8UhfoKnE7Jx+mU/Grbs7aSQ+toA62jNbwcreHtaAOt099fPTXWcLSx4uN4mwEGWSILI4TAmoOJ+PevcSirqHzAwYoJndGnDbsSEFHzYm2lQFgrR4S1cqwyX1duQPK1EsRnFyMhpxjx2SVI+Ov7tHwddOVGxGcXIz67uNZtK+UyuNip4GavhptGDTc7VeVXexVc7dSm793t1XC2U8FKwacgmiMGWSILcq24DK/+eBK/x1U+PnJIOw8se7gTXOxUEldGRHT3WFspEOypQbCnptoyfYUBGfl6pOaXIi2/FKl5OqTllyItT4fU/Mrv80rKUWEUyCzUI7NQD6Tdfp/OtlZws1fDw0ENd3s1PBys4aFRoyi7FGq/jigoB/TlBqiUcnZruIsYZIksxIHL2Xjp+xhkFOihUsjxxsh2mNIngL8wqdmLi4uTuoQm05zfm1TUSgX8XG3h52pba5uyCiNyivXILixDdrEe2YV6ZBeVIadIj+yiyu+vf71WrIdRALkl5cgtKcfFzKJq2/N6NBI70oAdaVdgpZDBwdoKGmtl5Vebyq/Otio421pBySu7jYpBlsjMVRiMeP+Pi/ho1yUIAbR2t8OHj3ZBqLfj7VcmsmAF17IAAI8//rjElTS9oqLq4Yiajkp5vQ+tzW3bGowCeSVlyC4qQ1ahHllFOmQW6JH119XcK2nZOBF3GbZuPigXMpQbBHKKy5BTXFbj9jTWSrjYquBsp4KrnQruGjVc7VVQyhlwG4JBlsiMJV8rwax1J3A8KQ8AMCHCF/Mf6ABbFf/pUvNXWlQAABj13JtoG95N4mqaRtyRPdi6+n3odDqpS6FaKOQyuNqr4WqvRluv6l0Zjh8/jm4vD8OcjzfAs3V7FOkqUKArR4GuAoV/fc0vKUduSRn0FUYU6ipQqKtA4rW/xw6WywBXOzXcNWp4aNTQOlrDTaOGnJ+43Rb/GhKZqS2n0vD6hlMo1FVAY61E5PiOuD/cW+qyiO46V2//Zjs0VUbSZalLoEZkpZDD2a7yauvNhBAoLTdUdlEoLkPuX1d5Mwsrb07LKtIjq0iPs3/111Up5PB2skYrZxv4ONnCXaPmqDQ1YJAlMjMlZRX45y9nse5o5diwXfyc8MHELvB1qb2/FxERmTeZTAZblRK2KiVaOf3dpUEIgUJ9RWVXhQI9Mgp1SMvTocxgREJOCRJySgDkwEohg5+L7V/j5trBTs0IBzDIEpmVmOQ8zPk+BleyK8eGnTGwDWbdG8xhX4iImimZrPLmMAdrKwS52wMAjEIgu1CPq3mlSM0rRUpuKXQVRlzOKsblrMohxTw0agS62aG1m12LfowvgyyRGSg3GPHxrkv4cOclGIwCXg7WWP5IJ44NS0TUAsllssrhvRys0dXPGUIIZBXqEZ9TOTZuRoHeNHTY4fhrcLK1QltPDdp6amrs1tCcMcgSSexKVhFeWn8SJ5PzAACjO3lj0ZgwONpaSVsYERGZBdkNwbZnoCuK9RV/PQiiGAk5JcgrKcfh+Gs4HH8NHhp1Zaj10rSI7gfN/x0SmSkhBL49nIR/b4lDabkBDtZK/GtsGMZ0biV1aUREZMbs1EqEejsi1NsRZRVGXMkqwrmMQiRdKzFdqd1/ORut3ezQsZUj/Fxsm23XAwZZIglkFurw6o+nsPt85TiZfYJc8e7DneDtdPsxDYmIiK5TKeVop3VAO60DSsoqcCmzCOfSC5GWrzP1qXWwViK0lSNCtQ7N7ipt83o3RBZg25k0zNtwGrkl5VAp5XhteDs82ScAcg6rQkREd8BWpUS4jxPCfZyQXaTHmZR8xKUXokBXgYOXc3D4Sg6CPTXo6ucED4211OU2CgZZorskp0iPBb+cxS8nUwEA7bUOWDGhc40DbBMREd0JN3s1Brb1QN82briYWYQzKflIy9fhfHohzqcXwsfJBl38nRDoamfR3Q7MOsguWLAACxcurDLP09MT6enpElVEVH9CCGw5nYb5P8cip7gMchnw3IAgzL43GGqlQuryiIioGbNSyNFB64AOWgdkFOhwIikPFzILcTWvFFfzSuFsa4Wufs5op9VY5GNyzTrIAkBoaCh+//1302uFgn/4yXJkFurw9qZYbIut/M9XW08Nlj0cjnAfJ2kLIyKiFsfTwRrDw7zQV+eKmOQ8nEkpQG5JOf44l4nD8dcQ4e+MUG8HKC1o7HKzD7JKpRJeXl5Sl0FUL0IIbIpJwcJfziKvpBxKuQzTB7XBjEFBvApLRESS0lhboX+wO3oEuiA2tQDHk3JRpK/A7gtZOJJwDd38ndGxlaNFPIzH7IPsxYsX4e3tDbVajZ49e2Lx4sVo3bp1re31ej30er3pdUFBwd0ok8gkPV+HNzeexh/nMgEAod4OWPpQOEK9HSWujIhIGnFxcVKX0GQs+b2plQp09XNGeCtHnE0rQHRiLgp1Fdh3MRvRCbno6u+ETmb+CaJZB9mePXtizZo1CAkJQUZGBhYtWoQ+ffogNjYWrq6uNa4TGRlZrV8t0d1gNAp8H52Mxb/GoVBXASuFDLOGBOO5AUEW8b9aIqLGVnCtcojBxx9/XOJKml5RUZHUJTSYUiFHuI8TQr0dEfdXoM0vLcefl3JwPDEPwXZyQGGeD+kx6yA7YsQI0/cdO3ZE7969ERQUhNWrV2POnDk1rjNv3rwqywoKCuDr69vktVLLdi69AG9sOI3jSXkAgE4+jlj2cCeEeHJEAiJquUqLKj8VHfXcm2gb3k3iappG3JE92Lr6feh0OqlLuWMKuQxhrRzRQeuAc+mFOByfgwJdBU7lKeH95AcwGIXUJVZj1kH2ZnZ2dujYsSMuXrxYaxu1Wg21Wn0Xq6KWrKSsAu//fhFf7o+HwShgp1LgpaEhmNonwKI6yxMRNSVXb3/4BIdKXUaTyEi6LHUJjU4ul6GDtwPaemlwNq0ABy9mIO/cfijkPaQurRqLCrJ6vR5xcXHo37+/1KUQ4fezGZi/ORYpeaUAgOGhXpj/QAdoHfl0LiIisnwKuQwdWznCofgqPjj8I4CaPw2XklkH2blz52L06NHw8/NDZmYmFi1ahIKCAkyZMkXq0qgFu5xVhEX/O4tdfz1etpWTDf45JhRD2ntKXBkREVHjU8gAUa6/fUMJmHWQvXr1Kh599FFkZ2fD3d0dvXr1wqFDh+Dv7y91adQCFejK8eEfFxH1ZwIqjAJWChmm9WuNF4e0ga3KrP8pERERNUtm/dd33bp1UpdABKNR4IdjyVj223lkF5UBAAa388D/jWqP1u72EldHRETUcpl1kCWS2v6L2XhnWxzOpFTeedva3Q5v3d8Bg9p6SFwZERERMcgS1eBMSj6WbDuHfRezAQAatRKz7g3GE70DoFJyNAIiIiJzwCBLdIPkayV4d/t5/ByTCgCwUsjweC9/zBzUBq72HNaNiIjInDDIEgFIyy/Fyt2X8d2RJJQbKgd8HtPZGy8PbQs/V1uJqyMiIqKaMMhSi5aaV4pPdl/C+qNXUWYwAgD6B7vhteHtENbKUeLqiIiI6FYYZKlFSskrxSe7LmF9dLLpCmzPQBfMujcYfYLcJK6OiIiI6oJBllqUc+kF+GJvPDafTDEF2F6tXTBrSAh6B7lKXB0RERHVB4MsNXtCCOy/lI3P914xjUIAAL1bu2L2vcHo2ZoBloiIyBIxyFKzpSs34H+n0vDlvis4l14IAJDLgBEdtXimf2t09nWStkAiIiK6Iwyy1OzEZxfj20OJ+PH4VeSVlAMAbFUKPBLhi2n9AuHrwlEIiIiImgMGWWoWyg1G/H42A98eTsL+S393H2jlZINJPf3wWE8/ONmqJKyQiIiIGhuDLFksIQROp+Rjw/EU/HIyFTnFZQAAmQwY1NYDj/X0w8C2HlDIZRJXSkRERE2BQZYsTmpeKTbFpGDD8RRcyiwyzXezV2NCdx9M7O7H7gNEREQtAIMsWYTkayXYdiYdW8+k4XhSnmm+WinHsFAvjO/SCv2D3aBUyKUrkoiIiO4qBlkyS0IIXM4qxm+xleH1TEpBleU9A13wYFcfDO/oBQdrK4mqJCIiIikxyFKDJCUlITs7+/YN60FXYcTpzDIcT9PjRLoemcUG0zK5DOjgpkJPH2v0bGUNN1sFgCxcOpvVqDXcyM3NDX5+fk22fSIiIrozDLJUb0lJSWjXvj1KS0rubEMyOVRebWDtGwbrgM6w9u0ImfLvq6uiohy6pFMouXAAJRcPIb4kH1vusPb6sLG1xbm4OIZZIiIiM8UgS/WWnZ2N0pISPPbaMnj6BdV5PaMAcstkyNbLkKWTI0cvQ4WoOqKArULAy8YIT2sjPKwFlK07AgM7Aniukd/FrWUkXca3S15BdnY2gywREZGZYpClBvP0C4JPcGiNy4QQyC8tR3qBDhn5eqQX6JBVpIfBKKq0UyvlaOVkAx9nG/i72sHZ1goyGYfLIiIiottjkKU7ZjAKXCsuQ3aRHlmFemQV6ZFdpIeu3FitrbVVZXCtDK+2cLNXMbgSERFRgzDIUp3lFpfhSnYxdsWXwOmeKTiYpYQ+JxG5JWW46UIrAEAhk8FNo4KXgzW8HK3h5WANRxtecSUiIqLGwSBLJrpyA1LzSpGap0NqXilS/pris4txJasIuSXlpraOvR9GaikAVD5NS6WUw91eDXd7Ndw0KrjZq+Fqr4JSznFdiYiIqGkwyDaBphia6k7oKwTy9Qbk6YzI0xmRrzMi76/X10oNyC4xIqvEgAJ99a4AN3O1kcNJrkfMvu3oO/g+BAb4wcVWBY21slleaY2Li5O6hCbRXN8XERG1LAyyjazRhqa6mUwOmZUacrUd5Nb2N0wayK3tobC2q/L6+vcKOyfI1XV/XKuxrBQVBVkwFGSZvpbnpqL8WgoqclOQWK43tdXe2xsBrnaN+z7NRMG1yvFpH3/8cYkraVpFRUW3b0RERGSmGGQb2fWhqSa+9i5cWrVGhRGoELK/vv41GWV/fb1p2fX5NSwziDu72imHgFoBWCsE1PK/vv712lYhYKusHPrKSq6ATOYFwKvWbcUd2YOtq9+HTqe7o5rMWWlR5ZPERj33JtqGd5O4msbXEn6GRETU/DHINrLI/dfg9+pmHIQcSGn87ctlgFqpgLWVHGqlAmorOaytFLBW3vD6huW2qspJpZQ32kf/GUmXG2U7lsDV27/WIcYsWUv6GRIRUfNlEUH2k08+wbJly5CWlobQ0FCsWLEC/fv3l7qsGsllgEz29w1OVgoZrBRyWCnkUCnlsFLIoPrrdY3zlPK/vpfdsPzveQq5rFn2RSUiIiKqL7MPst9//z1mz56NTz75BH379sVnn32GESNG4OzZs2b5xKXnujnip3n3YcY7X8E/pANDJxEREVETMfuxkZYvX45p06bh6aefRvv27bFixQr4+vpi5cqVUpdWIydrBQzFuVDKwRBLRERE1ITMOsiWlZXh2LFjGDZsWJX5w4YNw4EDBySqioiIiIjMgVl3LcjOzobBYICnp2eV+Z6enkhPT69xHb1eD73+7yGi8vPzAQAFBQVNV+gNrg9ndPViLPSljTwEl5m4fqNQesIFXLar+9BelqS5v8fm/v4AvsfmoLm/P6D5v8fm/v6AlvEes67GA6jMOHcjT13fhxA1PDb0ZsKMpaSkCADiwIEDVeYvWrRItG3btsZ15s+fLwBw4sSJEydOnDhxsuApOTn5tlnRrK/Iurm5QaFQVLv6mpmZWe0q7XXz5s3DnDlzTK+NRiOuXbsGV1fXu9JntaCgAL6+vkhOToaDg0OT78+S8NjUjsemdjw2teOxqRmPS+14bGrHY1O7u31shBAoLCyEt7f3bduadZBVqVTo1q0bduzYgXHjxpnm79ixA2PGjKlxHbVaDbVaXWWek5NTU5ZZIwcHB/5DqAWPTe14bGrHY1M7Hpua8bjUjsemdjw2tbubx8bR0bFO7cw6yALAnDlzMHnyZERERKB37974/PPPkZSUhOeff17q0oiIiIhIQmYfZCdMmICcnBz885//RFpaGsLCwvDrr7/C399f6tKIiIiISEJmH2QBYPr06Zg+fbrUZdSJWq3G/Pnzq3VvIB6bW+GxqR2PTe14bGrG41I7Hpva8djUzpyPjUyIuoxtQERERERkXsz6gQhERERERLVhkCUiIiIii8QgS0REREQWiUG2nvbu3YvRo0fD29sbMpkMmzZtuu06e/bsQbdu3WBtbY3WrVvj008/bfpCJVDfY7N7927IZLJq07lz5+5OwXdJZGQkunfvDo1GAw8PD4wdOxbnz5+/7Xot4bxpyLFpKefNypUrER4ebhq3sXfv3ti6dest12kJ50x9j0tLOV9qEhkZCZlMhtmzZ9+yXUs4b25Wl2PTUs6dBQsWVHuPXl5et1zHnM4ZBtl6Ki4uRqdOnfDRRx/VqX18fDxGjhyJ/v3748SJE3jjjTfw4osv4qeffmriSu+++h6b686fP4+0tDTTFBwc3EQVSmPPnj2YMWMGDh06hB07dqCiogLDhg1DcXFxreu0lPOmIcfmuuZ+3vj4+OCdd95BdHQ0oqOjMXjwYIwZMwaxsbE1tm8p50x9j8t1zf18udnRo0fx+eefIzw8/JbtWsp5c6O6HpvrWsK5ExoaWuU9nj59uta2ZnfO3PYhtlQrAGLjxo23bPPqq6+Kdu3aVZn33HPPiV69ejVhZdKry7HZtWuXACByc3PvSk3mIjMzUwAQe/bsqbVNSz1v6nJsWup5I4QQzs7O4ssvv6xxWUs9Z4S49XFpiedLYWGhCA4OFjt27BADBgwQs2bNqrVtSztv6nNsWsq5M3/+fNGpU6c6tze3c4ZXZJvYwYMHMWzYsCrz7rvvPkRHR6O8vFyiqsxLly5doNVqMWTIEOzatUvqcppcfn4+AMDFxaXWNi31vKnLsbmuJZ03BoMB69atQ3FxMXr37l1jm5Z4ztTluFzXks6XGTNmYNSoUbj33ntv27alnTf1OTbXtYRz5+LFi/D29kZgYCAmTpyIK1eu1NrW3M4Zi3gggiVLT0+Hp6dnlXmenp6oqKhAdnY2tFqtRJVJT6vV4vPPP0e3bt2g1+vx3//+F0OGDMHu3btxzz33SF1ekxBCYM6cOejXrx/CwsJqbdcSz5u6HpuWdN6cPn0avXv3hk6ng729PTZu3IgOHTrU2LYlnTP1OS4t6XwBgHXr1uH48eM4evRondq3pPOmvsempZw7PXv2xJo1axASEoKMjAwsWrQIffr0QWxsLFxdXau1N7dzhkH2LpDJZFVei7+eQXHz/Jambdu2aNu2rel17969kZycjHfffbdZ/ZK40cyZM3Hq1Cns37//tm1b2nlT12PTks6btm3bIiYmBnl5efjpp58wZcoU7Nmzp9bQ1lLOmfocl5Z0viQnJ2PWrFnYvn07rK2t67xeSzhvGnJsWsq5M2LECNP3HTt2RO/evREUFITVq1djzpw5Na5jTucMuxY0MS8vL6Snp1eZl5mZCaVSWeP/dFq6Xr164eLFi1KX0SReeOEFbN68Gbt27YKPj88t27a086Y+x6YmzfW8UalUaNOmDSIiIhAZGYlOnTrh/fffr7FtSzpn6nNcatJcz5djx44hMzMT3bp1g1KphFKpxJ49e/DBBx9AqVTCYDBUW6elnDcNOTY1aa7nzo3s7OzQsWPHWt+nuZ0zvCLbxHr37o1ffvmlyrzt27cjIiICVlZWElVlvk6cONGsPsoCKv+n+sILL2Djxo3YvXs3AgMDb7tOSzlvGnJsatIcz5uaCCGg1+trXNZSzpma3Oq41KS5ni9Dhgypdrf5k08+iXbt2uG1116DQqGotk5LOW8acmxq0lzPnRvp9XrExcWhf//+NS43u3NGklvMLFhhYaE4ceKEOHHihAAgli9fLk6cOCESExOFEEK8/vrrYvLkyab2V65cEba2tuKll14SZ8+eFV999ZWwsrISP/74o1RvocnU99j85z//ERs3bhQXLlwQZ86cEa+//roAIH766Sep3kKT+Mc//iEcHR3F7t27RVpammkqKSkxtWmp501Djk1LOW/mzZsn9u7dK+Lj48WpU6fEG2+8IeRyudi+fbsQouWeM/U9Li3lfKnNzXfmt9Tzpia3OzYt5dx5+eWXxe7du8WVK1fEoUOHxP333y80Go1ISEgQQpj/OcMgW0/Xh+O4eZoyZYoQQogpU6aIAQMGVFln9+7dokuXLkKlUomAgACxcuXKu1/4XVDfY7NkyRIRFBQkrK2thbOzs+jXr5/YsmWLNMU3oZqOCQARFRVlatNSz5uGHJuWct489dRTwt/fX6hUKuHu7i6GDBliCmtCtNxzpr7HpaWcL7W5Oay11POmJrc7Ni3l3JkwYYLQarXCyspKeHt7i/Hjx4vY2FjTcnM/Z2RC/NVDl4iIiIjIgvBmLyIiIiKySAyyRERERGSRGGSJiIiIyCIxyBIRERGRRWKQJSIiIiKLxCBLRERERBaJQZaIiIiILBKDLBERERFZJAZZIiIzMnDgQMyePdv0OiAgACtWrJCsHiIic8YgS0TNwtSpUyGTyfD8889XWzZ9+nTIZDJMnTr17hd2k1WrVsHJyanW5Rs2bMC//vWvJq9DJpNh06ZNt223a9cuDBo0CC4uLrC1tUVwcDCmTJmCioqKJq+RiOh2GGSJqNnw9fXFunXrUFpaapqn0+nw3Xffwc/PT8LK6s7FxQUajabJtl9WVlbntrGxsRgxYgS6d++OvXv34vTp0/jwww9hZWUFo9HYJPUJIRiSiajOGGSJqNno2rUr/Pz8sGHDBtO8DRs2wNfXF126dKnSVgiBpUuXonXr1rCxsUGnTp3w448/mpYbDAZMmzYNgYGBsLGxQdu2bfH+++9X2cbUqVMxduxYvPvuu9BqtXB1dcWMGTNQXl7e4Pdwc9eCm0VFRcHR0RE7duwAAJw9exYjR46Evb09PD09MXnyZGRnZ1fZ3syZMzFnzhy4ublh6NChCAgIAACMGzcOMpnM9PpmO3bsgFarxdKlSxEWFoagoCAMHz4cX375JVQqlandn3/+iQEDBsDW1hbOzs647777kJubCwDQ6/V48cUX4eHhAWtra/Tr1w9Hjx41rbt7927IZDL89ttviIiIgFqtxr59+2778yEiAhhkiaiZefLJJxEVFWV6/fXXX+Opp56q1u7//u//EBUVhZUrVyI2NhYvvfQSHn/8cezZswcAYDQa4ePjg/Xr1+Ps2bN4++238cYbb2D9+vVVtrNr1y5cvnwZu3btwurVq7Fq1SqsWrWqSd7bu+++i7lz5+K3337D0KFDkZaWhgEDBqBz586Ijo7Gtm3bkJGRgUceeaTKeqtXr4ZSqcSff/6Jzz77zBQko6KikJaWViVY3sjLywtpaWnYu3dvrTXFxMRgyJAhCA0NxcGDB7F//36MHj0aBoMBAPDqq6/ip59+wurVq3H8+HG0adMG9913H65du1ZlO6+++ioiIyMRFxeH8PDw2/58iIgAAIKIqBmYMmWKGDNmjMjKyhJqtVrEx8eLhIQEYW1tLbKyssSYMWPElClThBBCFBUVCWtra3HgwIEq25g2bZp49NFHa93H9OnTxYMPPlhln/7+/qKiosI07+GHHxYTJkyodRtRUVHC0dGx1uUDBgwQs2bNMr329/cX//nPf8Trr78utFqtOHXqlGnZW2+9JYYNG1Zl/eTkZAFAnD9/3rS9zp07V9sPALFx48Za6xBCiIqKCjF16lQBQHh5eYmxY8eKDz/8UOTn55vaPProo6Jv3741rl9UVCSsrKzEt99+a5pXVlYmvL29xdKlS4UQQuzatUsAEJs2baqyXkN+PkTU8iiljdFERI3Lzc0No0aNwurVqyGEwKhRo+Dm5lalzdmzZ6HT6TB06NAq88vKyqp0Qfj000/x5ZdfIjExEaWlpSgrK0Pnzp2rrBMaGgqFQmF6rdVqcfr06UZ9T++99x6Ki4sRHR2N1q1bm+YfO3YMu3btgr29fbV1Ll++jJCQEABAREREg/arUCgQFRWFRYsWYefOnTh06BD+/e9/Y8mSJThy5Ai0Wi1iYmLw8MMP17j+5cuXUV5ejr59+5rmWVlZoUePHoiLi6vS9sYa6/rzISJikCWiZuepp57CzJkzAQAff/xxteXXb1TasmULWrVqVWWZWq0GAKxfvx4vvfQS3nvvPfTu3RsajQbLli3D4cOHq7S3srKq8lomkzX6jVD9+/fHli1bsH79erz++utV3sfo0aOxZMmSautotVrT93Z2dne0/1atWmHy5MmYPHkyFi1ahJCQEHz66adYuHAhbGxsal1PCAGg8pjcPP/meTfWWJefDxERwCBLRM3Q8OHDTXfn33fffdWWd+jQAWq1GklJSRgwYECN29i3bx/69OmD6dOnm+Zdvny5aQq+jR49euCFF17AfffdB4VCgVdeeQVA5c1tP/30EwICAqBU1u/XuZWVlakfa304OztDq9WiuLgYABAeHo4//vgDCxcurNa2TZs2UKlU2L9/PyZNmgQAKC8vR3R09C1vaKvLz4eICGCQJaJmSKFQmD66vvFj/+s0Gg3mzp2Ll156CUajEf369UNBQQEOHDgAe3t7TJkyBW3atMGaNWvw22+/ITAwEP/9739x9OhRBAYG3nF9BoMBMTExVeapVCp06NCh1nV69+6NrVu3Yvjw4VAqlXjppZcwY8YMfPHFF3j00UfxyiuvwM3NDZcuXcK6devwxRdf1PjerwsICMAff/yBvn37Qq1Ww9nZuVqbzz77DDExMRg3bhyCgoKg0+mwZs0axMbG4sMPPwQAzJs3Dx07dsT06dPx/PPPQ6VSYdeuXXj44Yfh5uaGf/zjH3jllVfg4uICPz8/LF26FCUlJZg2bVqttdXl50NEBDDIElEz5eDgcMvl//rXv+Dh4YHIyEhcuXIFTk5O6Nq1K9544w0AwPPPP4+YmBhMmDABMpkMjz76KKZPn46tW7fecW1FRUXV+nr6+/sjISHhluv17dsXW7ZswciRI6FQKPDiiy/izz//xGuvvYb77rsPer0e/v7+GD58OOTyWw9K895772HOnDn44osv0KpVqxr33aNHD+zfvx/PP/88UlNTYW9vj9DQUGzatMl0pTQkJATbt2/HG2+8gR49esDGxgY9e/bEo48+CgB45513YDQaMXnyZBQWFiIiIgK//fZbjcH5Rrf7+RARAYBMXO/ERERERERkQTiOLBERERFZJAZZIiIiIrJIDLJEREREZJEYZImIiIjIIjHIEhEREZFFYpAlIiIiIovEIEtEREREFolBloiIiIgsEoMsEREREVkkBlkiIiIiskgMskRERERkkRhkiYiIiMgi/T9w6zhDM7mEHAAAAABJRU5ErkJggg==", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Construct distribution plots\n", "for col in construct_score_columns:\n", "\n", " plt.figure(figsize=(7, 4))\n", "\n", " sns.histplot(\n", " df[col].dropna(),\n", " bins=10,\n", " kde=True\n", " )\n", "\n", " plt.title(f\"Distribution of {col}\")\n", " plt.xlabel(\"Mean Likert Score\")\n", " plt.ylabel(\"Frequency\")\n", " plt.tight_layout()\n", " plt.show()" ] }, { "cell_type": "markdown", "id": "4dc51660-3fb5-4b70-b93f-56a1df0b8faa", "metadata": {}, "source": [ "# Correlation analysis — Pearson and Spearman" ] }, { "cell_type": "code", "execution_count": 29, "id": "1ec6bcd0-4e92-4340-bf50-6c80bf89f168", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pearson correlation matrix:\n" ] }, { "data": { "text/html": [ "
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OR_ScoreTC_ScoreEKS_ScoreIRC_ScoreDFR_Score
OR_Score1.0000.6350.6090.5830.547
TC_Score0.6351.0000.5770.7150.632
EKS_Score0.6090.5771.0000.5960.647
IRC_Score0.5830.7150.5961.0000.567
DFR_Score0.5470.6320.6470.5671.000
\n", "
" ], "text/plain": [ " OR_Score TC_Score EKS_Score IRC_Score DFR_Score\n", "OR_Score 1.000 0.635 0.609 0.583 0.547\n", "TC_Score 0.635 1.000 0.577 0.715 0.632\n", "EKS_Score 0.609 0.577 1.000 0.596 0.647\n", "IRC_Score 0.583 0.715 0.596 1.000 0.567\n", "DFR_Score 0.547 0.632 0.647 0.567 1.000" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "\n", "Spearman correlation matrix:\n" ] }, { "data": { "text/html": [ "
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OR_ScoreTC_ScoreEKS_ScoreIRC_ScoreDFR_Score
OR_Score1.0000.5040.5120.4760.404
TC_Score0.5041.0000.5080.6600.498
EKS_Score0.5120.5081.0000.5210.569
IRC_Score0.4760.6600.5211.0000.434
DFR_Score0.4040.4980.5690.4341.000
\n", "
" ], "text/plain": [ " OR_Score TC_Score EKS_Score IRC_Score DFR_Score\n", "OR_Score 1.000 0.504 0.512 0.476 0.404\n", "TC_Score 0.504 1.000 0.508 0.660 0.498\n", "EKS_Score 0.512 0.508 1.000 0.521 0.569\n", "IRC_Score 0.476 0.660 0.521 1.000 0.434\n", "DFR_Score 0.404 0.498 0.569 0.434 1.000" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "analysis_constructs = [\n", " \"OR_Score\",\n", " \"TC_Score\",\n", " \"EKS_Score\",\n", " \"IRC_Score\",\n", " \"DFR_Score\"\n", "]\n", "\n", "\n", "pearson_corr = df[\n", " analysis_constructs\n", "].corr(method=\"pearson\")\n", "\n", "\n", "spearman_corr = df[\n", " analysis_constructs\n", "].corr(method=\"spearman\")\n", "\n", "\n", "print(\"Pearson correlation matrix:\")\n", "display(pearson_corr.round(3))\n", "\n", "print(\"\\nSpearman correlation matrix:\")\n", "display(spearman_corr.round(3))" ] }, { "cell_type": "code", "execution_count": 30, "id": "d722ebaf-a38b-419b-a93a-ed5f12fea9ab", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pearson p-values:\n" ] }, { "data": { "text/html": [ "
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OR_ScoreTC_ScoreEKS_ScoreIRC_ScoreDFR_Score
OR_Score0.00.00.00.00.0
TC_Score0.00.00.00.00.0
EKS_Score0.00.00.00.00.0
IRC_Score0.00.00.00.00.0
DFR_Score0.00.00.00.00.0
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" ], "text/plain": [ " OR_Score TC_Score EKS_Score IRC_Score DFR_Score\n", "OR_Score 0.0 0.0 0.0 0.0 0.0\n", "TC_Score 0.0 0.0 0.0 0.0 0.0\n", "EKS_Score 0.0 0.0 0.0 0.0 0.0\n", "IRC_Score 0.0 0.0 0.0 0.0 0.0\n", "DFR_Score 0.0 0.0 0.0 0.0 0.0" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "\n", "Spearman p-values:\n" ] }, { "data": { "text/html": [ "
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OR_ScoreTC_ScoreEKS_ScoreIRC_ScoreDFR_Score
OR_Score0.00.00.00.00.0
TC_Score0.00.00.00.00.0
EKS_Score0.00.00.00.00.0
IRC_Score0.00.00.00.00.0
DFR_Score0.00.00.00.00.0
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" ], "text/plain": [ " OR_Score TC_Score EKS_Score IRC_Score DFR_Score\n", "OR_Score 0.0 0.0 0.0 0.0 0.0\n", "TC_Score 0.0 0.0 0.0 0.0 0.0\n", "EKS_Score 0.0 0.0 0.0 0.0 0.0\n", "IRC_Score 0.0 0.0 0.0 0.0 0.0\n", "DFR_Score 0.0 0.0 0.0 0.0 0.0" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Correlation p-values\n", "def correlation_pvalues(data, method=\"pearson\"):\n", "\n", " cols = data.columns\n", "\n", " p_values = pd.DataFrame(\n", " np.ones((len(cols), len(cols))),\n", " index=cols,\n", " columns=cols\n", " )\n", "\n", " for i in range(len(cols)):\n", "\n", " for j in range(len(cols)):\n", "\n", " if i == j:\n", " p_values.iloc[i, j] = 0\n", "\n", " else:\n", "\n", " x = data.iloc[:, i]\n", " y = data.iloc[:, j]\n", "\n", " valid = x.notna() & y.notna()\n", "\n", " if valid.sum() >= 3:\n", "\n", " if method == \"pearson\":\n", "\n", " _, p = stats.pearsonr(\n", " x[valid],\n", " y[valid]\n", " )\n", "\n", " else:\n", "\n", " _, p = stats.spearmanr(\n", " x[valid],\n", " y[valid]\n", " )\n", "\n", " p_values.iloc[i, j] = p\n", "\n", " return p_values\n", "\n", "\n", "pearson_p = correlation_pvalues(\n", " df[analysis_constructs],\n", " method=\"pearson\"\n", ")\n", "\n", "spearman_p = correlation_pvalues(\n", " df[analysis_constructs],\n", " method=\"spearman\"\n", ")\n", "\n", "print(\"Pearson p-values:\")\n", "display(pearson_p.round(4))\n", "\n", "print(\"\\nSpearman p-values:\")\n", "display(spearman_p.round(4))" ] }, { "cell_type": "code", "execution_count": 31, "id": "45d39654-73f3-4f74-a736-ed0aed1c1e8c", "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Correlation heatmap\n", "display_names = {\n", " \"OR_Score\": \"Organisational Readiness\",\n", " \"TC_Score\": \"Technical Capability\",\n", " \"EKS_Score\": \"Employee Knowledge & Skills\",\n", " \"IRC_Score\": \"Incident Response Capability\",\n", " \"DFR_Score\": \"Digital Forensic Readiness\"\n", "}\n", "\n", "heatmap_data = spearman_corr.rename(\n", " index=display_names,\n", " columns=display_names\n", ")\n", "\n", "plt.figure(figsize=(10, 7))\n", "\n", "sns.heatmap(\n", " heatmap_data,\n", " annot=True,\n", " fmt=\".2f\",\n", " cmap=\"coolwarm\",\n", " center=0,\n", " square=True\n", ")\n", "\n", "plt.title(\n", " \"Spearman Correlation Matrix of Study Constructs\"\n", ")\n", "\n", "plt.tight_layout()\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 32, "id": "a2edcb93-e1cc-4c89-a51a-3dd416e4f05c", "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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", 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", 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Scatterplots against DFR\n", "predictors = [\n", " \"OR_Score\",\n", " \"TC_Score\",\n", " \"EKS_Score\",\n", " \"IRC_Score\"\n", "]\n", "\n", "\n", "for predictor in predictors:\n", "\n", " plot_data = df[\n", " [predictor, \"DFR_Score\"]\n", " ].dropna()\n", "\n", " plt.figure(figsize=(7, 5))\n", "\n", " sns.regplot(\n", " data=plot_data,\n", " x=predictor,\n", " y=\"DFR_Score\",\n", " scatter_kws={\"alpha\": 0.6}\n", " )\n", "\n", " plt.title(\n", " f\"{predictor} and Digital Forensic Readiness\"\n", " )\n", "\n", " plt.xlabel(display_names[predictor])\n", " plt.ylabel(\"Digital Forensic Readiness\")\n", "\n", " plt.tight_layout()\n", " plt.show()" ] }, { "cell_type": "markdown", "id": "1d03d384-ea28-4162-9e51-3e08980dcf3e", "metadata": {}, "source": [ "# Prepare data for multiple regression" ] }, { "cell_type": "code", "execution_count": 33, "id": "cc828d10-4040-4eca-807a-de922b8bcbb9", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Regression sample size: 102\n" ] }, { "data": { "text/html": [ "
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DFR_ScoreOR_ScoreTC_ScoreEKS_ScoreIRC_Score
03.22.62.62.82.8
12.23.02.62.82.6
22.42.42.62.82.6
32.42.82.42.01.8
41.62.62.42.22.6
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" ], "text/plain": [ " DFR_Score OR_Score TC_Score EKS_Score IRC_Score\n", "0 3.2 2.6 2.6 2.8 2.8\n", "1 2.2 3.0 2.6 2.8 2.6\n", "2 2.4 2.4 2.6 2.8 2.6\n", "3 2.4 2.8 2.4 2.0 1.8\n", "4 1.6 2.6 2.4 2.2 2.6" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# REGRESSION DATASET\n", "regression_variables = [\n", " \"DFR_Score\",\n", " \"OR_Score\",\n", " \"TC_Score\",\n", " \"EKS_Score\",\n", " \"IRC_Score\"\n", "]\n", "\n", "regression_df = df[\n", " regression_variables\n", "].dropna().copy()\n", "\n", "print(\n", " \"Regression sample size:\",\n", " len(regression_df)\n", ")\n", "\n", "display(regression_df.head())" ] }, { "cell_type": "code", "execution_count": 34, "id": "b68ec628-d3b4-4b82-99d5-4df7ae5bb386", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Number of predictors: 4\n", "Conservative minimum cases-per-predictor benchmark: 40\n", "Actual regression cases: 102\n", "\n", "Regression sample size is adequate for exploratory four-predictor analysis under this benchmark.\n" ] } ], "source": [ "# Check regression sample size\n", "number_of_predictors = 4\n", "minimum_cases_per_predictor = 10\n", "\n", "recommended_minimum = (\n", " number_of_predictors *\n", " minimum_cases_per_predictor\n", ")\n", "\n", "print(\n", " \"Number of predictors:\",\n", " number_of_predictors\n", ")\n", "\n", "print(\n", " \"Conservative minimum cases-per-predictor benchmark:\",\n", " recommended_minimum\n", ")\n", "\n", "print(\n", " \"Actual regression cases:\",\n", " len(regression_df)\n", ")\n", "\n", "if len(regression_df) < recommended_minimum:\n", "\n", " print(\n", " \"\\nWARNING: The available sample is relatively small \"\n", " \"for a four-predictor regression model.\"\n", " )\n", "\n", " print(\n", " \"Regression can still be exploratory, but coefficients \"\n", " \"and significance tests should be interpreted cautiously.\"\n", " )\n", "\n", "else:\n", "\n", " print(\n", " \"\\nRegression sample size is adequate for exploratory \"\n", " \"four-predictor analysis under this benchmark.\"\n", " )" ] }, { "cell_type": "markdown", "id": "c49c802b-1a11-457a-85e0-31ea8f397fab", "metadata": {}, "source": [ "# Fit multiple linear regression" ] }, { "cell_type": "code", "execution_count": 35, "id": "e4166f7c-a98c-4e2c-b8b5-595f85f26f34", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " OLS Regression Results \n", "==============================================================================\n", "Dep. Variable: DFR_Score R-squared: 0.525\n", "Model: OLS Adj. R-squared: 0.505\n", "Method: Least Squares F-statistic: 26.75\n", "Date: Thu, 10 Sep 2026 Prob (F-statistic): 5.81e-15\n", "Time: 18:25:59 Log-Likelihood: -86.514\n", "No. Observations: 102 AIC: 183.0\n", "Df Residuals: 97 BIC: 196.2\n", "Df Model: 4 \n", "Covariance Type: nonrobust \n", "==============================================================================\n", " coef std err t P>|t| [0.025 0.975]\n", "------------------------------------------------------------------------------\n", "const 0.4126 0.289 1.428 0.157 -0.161 0.986\n", "OR_Score 0.0837 0.110 0.759 0.450 -0.135 0.302\n", "TC_Score 0.3396 0.118 2.875 0.005 0.105 0.574\n", "EKS_Score 0.3753 0.096 3.901 0.000 0.184 0.566\n", "IRC_Score 0.0761 0.109 0.698 0.487 -0.140 0.293\n", "==============================================================================\n", "Omnibus: 6.881 Durbin-Watson: 2.053\n", "Prob(Omnibus): 0.032 Jarque-Bera (JB): 6.738\n", "Skew: -0.472 Prob(JB): 0.0344\n", "Kurtosis: 3.833 Cond. No. 34.0\n", "==============================================================================\n", "\n", "Notes:\n", "[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n" ] } ], "source": [ "X = regression_df[\n", " predictors\n", "]\n", "\n", "y = regression_df[\n", " \"DFR_Score\"\n", "]\n", "\n", "X = sm.add_constant(X)\n", "\n", "ols_model = sm.OLS(\n", " y,\n", " X\n", ").fit()\n", "\n", "print(\n", " ols_model.summary()\n", ")" ] }, { "cell_type": "code", "execution_count": 36, "id": "a847027e-2af5-4f71-893f-8433d099efbb", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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BSEtpCI_LowerCI_UpperSignificant_p<.05
const0.41260.28891.42800.1565-0.16090.9860False
OR_Score0.08370.11020.75920.4496-0.13510.3024False
TC_Score0.33960.11812.87490.00500.10520.5741True
EKS_Score0.37530.09623.90080.00020.18440.5663True
IRC_Score0.07610.10900.69830.4867-0.14030.2925False
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" ], "text/plain": [ " B SE t p CI_Lower CI_Upper Significant_p<.05\n", "const 0.4126 0.2889 1.4280 0.1565 -0.1609 0.9860 False\n", "OR_Score 0.0837 0.1102 0.7592 0.4496 -0.1351 0.3024 False\n", "TC_Score 0.3396 0.1181 2.8749 0.0050 0.1052 0.5741 True\n", "EKS_Score 0.3753 0.0962 3.9008 0.0002 0.1844 0.5663 True\n", "IRC_Score 0.0761 0.1090 0.6983 0.4867 -0.1403 0.2925 False" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Regression coefficient table\n", "coefficient_table = pd.DataFrame({\n", " \"B\": ols_model.params,\n", " \"SE\": ols_model.bse,\n", " \"t\": ols_model.tvalues,\n", " \"p\": ols_model.pvalues,\n", " \"CI_Lower\": ols_model.conf_int()[0],\n", " \"CI_Upper\": ols_model.conf_int()[1]\n", "})\n", "\n", "coefficient_table[\"Significant_p<.05\"] = (\n", " coefficient_table[\"p\"] < 0.05\n", ")\n", "\n", "display(\n", " coefficient_table.round(4)\n", ")" ] }, { "cell_type": "code", "execution_count": 37, "id": "e9f6d17c-6fa2-4a42-8be3-39c40b6d8b4a", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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StatisticValue
0N102.0000
1R-squared0.5245
2Adjusted R-squared0.5049
3F-statistic26.7492
4F-test p-value0.0000
5AIC183.0285
6BIC196.1534
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" ], "text/plain": [ " Statistic Value\n", "0 N 102.0000\n", "1 R-squared 0.5245\n", "2 Adjusted R-squared 0.5049\n", "3 F-statistic 26.7492\n", "4 F-test p-value 0.0000\n", "5 AIC 183.0285\n", "6 BIC 196.1534" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Regression model statistics\n", "model_statistics = pd.DataFrame({\n", " \"Statistic\": [\n", " \"N\",\n", " \"R-squared\",\n", " \"Adjusted R-squared\",\n", " \"F-statistic\",\n", " \"F-test p-value\",\n", " \"AIC\",\n", " \"BIC\"\n", " ],\n", " \"Value\": [\n", " int(ols_model.nobs),\n", " ols_model.rsquared,\n", " ols_model.rsquared_adj,\n", " ols_model.fvalue,\n", " ols_model.f_pvalue,\n", " ols_model.aic,\n", " ols_model.bic\n", " ]\n", "})\n", "\n", "display(\n", " model_statistics.round(4)\n", ")" ] }, { "cell_type": "code", "execution_count": 38, "id": "0edd3ae9-80c8-46a9-868f-9b434e4391ea", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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PredictorStandardised_Betap_value
0OR_Score0.07520.4496
1TC_Score0.31470.0050
2EKS_Score0.37470.0002
3IRC_Score0.07450.4867
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" ], "text/plain": [ " Predictor Standardised_Beta p_value\n", "0 OR_Score 0.0752 0.4496\n", "1 TC_Score 0.3147 0.0050\n", "2 EKS_Score 0.3747 0.0002\n", "3 IRC_Score 0.0745 0.4867" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# STANDARDISED BETA COEFFICIENTS\n", "standardised_data = regression_df.copy()\n", "\n", "for col in standardised_data.columns:\n", "\n", " standardised_data[col] = (\n", " standardised_data[col] -\n", " standardised_data[col].mean()\n", " ) / standardised_data[col].std()\n", "\n", "\n", "X_std = standardised_data[predictors]\n", "y_std = standardised_data[\"DFR_Score\"]\n", "\n", "X_std = sm.add_constant(X_std)\n", "\n", "standardised_model = sm.OLS(\n", " y_std,\n", " X_std\n", ").fit()\n", "\n", "standardised_betas = pd.DataFrame({\n", " \"Predictor\": predictors,\n", " \"Standardised_Beta\": [\n", " standardised_model.params[p]\n", " for p in predictors\n", " ],\n", " \"p_value\": [\n", " standardised_model.pvalues[p]\n", " for p in predictors\n", " ]\n", "})\n", "\n", "display(\n", " standardised_betas.round(4)\n", ")" ] }, { "cell_type": "markdown", "id": "ef1f0a53-894f-4d09-b20a-dc8be55ecb49", "metadata": {}, "source": [ "# Multicollinearity — VIF, Residual histogram, Q-Q plot and Residuals vs fitted values" ] }, { "cell_type": "code", "execution_count": 39, "id": "37be9a26-05b0-4eed-a68d-4770fbdd0077", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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VariableVIF
0OR_Score35.863
1TC_Score46.597
2EKS_Score30.066
3IRC_Score39.041
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" ], "text/plain": [ " Variable VIF\n", "0 OR_Score 35.863\n", "1 TC_Score 46.597\n", "2 EKS_Score 30.066\n", "3 IRC_Score 39.041" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# VARIANCE INFLATION FACTOR\n", "vif_data = regression_df[predictors].copy()\n", "\n", "vif_table = pd.DataFrame({\n", " \"Variable\": predictors,\n", " \"VIF\": [\n", " variance_inflation_factor(\n", " vif_data.values,\n", " i\n", " )\n", " for i in range(vif_data.shape[1])\n", " ]\n", "})\n", "\n", "display(\n", " vif_table.round(3)\n", ")" ] }, { "cell_type": "code", "execution_count": 40, "id": "681f3c13-ca97-4ddd-86cc-9249deeea418", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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DFR_ScorePredicted_DFRResidual
03.22.7772270.422773
12.22.795464-0.595464
22.42.745266-0.345266
32.42.3496260.050374
41.62.468873-0.868873
\n", "
" ], "text/plain": [ " DFR_Score Predicted_DFR Residual\n", "0 3.2 2.777227 0.422773\n", "1 2.2 2.795464 -0.595464\n", "2 2.4 2.745266 -0.345266\n", "3 2.4 2.349626 0.050374\n", "4 1.6 2.468873 -0.868873" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Regression residuals\n", "\n", "regression_df[\"Predicted_DFR\"] = (\n", " ols_model.predict(X)\n", ")\n", "\n", "regression_df[\"Residual\"] = (\n", " regression_df[\"DFR_Score\"] -\n", " regression_df[\"Predicted_DFR\"]\n", ")\n", "\n", "display(\n", " regression_df[\n", " [\n", " \"DFR_Score\",\n", " \"Predicted_DFR\",\n", " \"Residual\"\n", " ]\n", " ].head()\n", ")" ] }, { "cell_type": "code", "execution_count": 41, "id": "0573b9c7-3a4f-41bd-bb55-f96af3e14a06", "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Residual histogram\n", "plt.figure(figsize=(7, 5))\n", "\n", "sns.histplot(\n", " regression_df[\"Residual\"],\n", " bins=12,\n", " kde=True\n", ")\n", "\n", "plt.title(\"Distribution of Regression Residuals\")\n", "plt.xlabel(\"Residual\")\n", "plt.ylabel(\"Frequency\")\n", "\n", "plt.tight_layout()\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 42, "id": "8e268378-85cd-4287-b052-af77a1938bfa", "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Q-Q plot\n", "plt.figure(figsize=(7, 5))\n", "\n", "stats.probplot(\n", " regression_df[\"Residual\"],\n", " dist=\"norm\",\n", " plot=plt\n", ")\n", "\n", "plt.title(\n", " \"Q-Q Plot of Regression Residuals\"\n", ")\n", "\n", "plt.tight_layout()\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 43, "id": "85d98dc5-ac20-467b-8760-aac14ff58997", "metadata": {}, "outputs": [ { "data": { "image/png": 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Residuals vs fitted values\n", "plt.figure(figsize=(7, 5))\n", "\n", "sns.scatterplot(\n", " x=regression_df[\"Predicted_DFR\"],\n", " y=regression_df[\"Residual\"]\n", ")\n", "\n", "plt.axhline(\n", " 0,\n", " linestyle=\"--\"\n", ")\n", "\n", "plt.title(\n", " \"Residuals versus Predicted Values\"\n", ")\n", "\n", "plt.xlabel(\"Predicted Digital Forensic Readiness\")\n", "plt.ylabel(\"Residual\")\n", "\n", "plt.tight_layout()\n", "plt.show()" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.12.7" } }, "nbformat": 4, "nbformat_minor": 5 }