You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
264 lines
7.5 KiB
264 lines
7.5 KiB
{
|
|
"cells": [
|
|
{
|
|
"cell_type": "markdown",
|
|
"source": [
|
|
"## Introduction to Probability and Statistics \n",
|
|
"## Assignment \n",
|
|
"\n",
|
|
"For dis assignment, we go use di dataset of diabetes patients wey dem collect [from here](https://www4.stat.ncsu.edu/~boos/var.select/diabetes.html). \n"
|
|
],
|
|
"metadata": {}
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 13,
|
|
"source": [
|
|
"import pandas as pd\n",
|
|
"import numpy as np\n",
|
|
"\n",
|
|
"df = pd.read_csv(\"../../data/diabetes.tsv\",sep='\\t')\n",
|
|
"df.head()"
|
|
],
|
|
"outputs": [
|
|
{
|
|
"output_type": "execute_result",
|
|
"data": {
|
|
"text/plain": [
|
|
" AGE SEX BMI BP S1 S2 S3 S4 S5 S6 Y\n",
|
|
"0 59 2 32.1 101.0 157 93.2 38.0 4.0 4.8598 87 151\n",
|
|
"1 48 1 21.6 87.0 183 103.2 70.0 3.0 3.8918 69 75\n",
|
|
"2 72 2 30.5 93.0 156 93.6 41.0 4.0 4.6728 85 141\n",
|
|
"3 24 1 25.3 84.0 198 131.4 40.0 5.0 4.8903 89 206\n",
|
|
"4 50 1 23.0 101.0 192 125.4 52.0 4.0 4.2905 80 135"
|
|
],
|
|
"text/html": [
|
|
"<div>\n",
|
|
"<style scoped>\n",
|
|
" .dataframe tbody tr th:only-of-type {\n",
|
|
" vertical-align: middle;\n",
|
|
" }\n",
|
|
"\n",
|
|
" .dataframe tbody tr th {\n",
|
|
" vertical-align: top;\n",
|
|
" }\n",
|
|
"\n",
|
|
" .dataframe thead th {\n",
|
|
" text-align: right;\n",
|
|
" }\n",
|
|
"</style>\n",
|
|
"<table border=\"1\" class=\"dataframe\">\n",
|
|
" <thead>\n",
|
|
" <tr style=\"text-align: right;\">\n",
|
|
" <th></th>\n",
|
|
" <th>AGE</th>\n",
|
|
" <th>SEX</th>\n",
|
|
" <th>BMI</th>\n",
|
|
" <th>BP</th>\n",
|
|
" <th>S1</th>\n",
|
|
" <th>S2</th>\n",
|
|
" <th>S3</th>\n",
|
|
" <th>S4</th>\n",
|
|
" <th>S5</th>\n",
|
|
" <th>S6</th>\n",
|
|
" <th>Y</th>\n",
|
|
" </tr>\n",
|
|
" </thead>\n",
|
|
" <tbody>\n",
|
|
" <tr>\n",
|
|
" <th>0</th>\n",
|
|
" <td>59</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>32.1</td>\n",
|
|
" <td>101.0</td>\n",
|
|
" <td>157</td>\n",
|
|
" <td>93.2</td>\n",
|
|
" <td>38.0</td>\n",
|
|
" <td>4.0</td>\n",
|
|
" <td>4.8598</td>\n",
|
|
" <td>87</td>\n",
|
|
" <td>151</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>1</th>\n",
|
|
" <td>48</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>21.6</td>\n",
|
|
" <td>87.0</td>\n",
|
|
" <td>183</td>\n",
|
|
" <td>103.2</td>\n",
|
|
" <td>70.0</td>\n",
|
|
" <td>3.0</td>\n",
|
|
" <td>3.8918</td>\n",
|
|
" <td>69</td>\n",
|
|
" <td>75</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>2</th>\n",
|
|
" <td>72</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>30.5</td>\n",
|
|
" <td>93.0</td>\n",
|
|
" <td>156</td>\n",
|
|
" <td>93.6</td>\n",
|
|
" <td>41.0</td>\n",
|
|
" <td>4.0</td>\n",
|
|
" <td>4.6728</td>\n",
|
|
" <td>85</td>\n",
|
|
" <td>141</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>3</th>\n",
|
|
" <td>24</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>25.3</td>\n",
|
|
" <td>84.0</td>\n",
|
|
" <td>198</td>\n",
|
|
" <td>131.4</td>\n",
|
|
" <td>40.0</td>\n",
|
|
" <td>5.0</td>\n",
|
|
" <td>4.8903</td>\n",
|
|
" <td>89</td>\n",
|
|
" <td>206</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>4</th>\n",
|
|
" <td>50</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>23.0</td>\n",
|
|
" <td>101.0</td>\n",
|
|
" <td>192</td>\n",
|
|
" <td>125.4</td>\n",
|
|
" <td>52.0</td>\n",
|
|
" <td>4.0</td>\n",
|
|
" <td>4.2905</td>\n",
|
|
" <td>80</td>\n",
|
|
" <td>135</td>\n",
|
|
" </tr>\n",
|
|
" </tbody>\n",
|
|
"</table>\n",
|
|
"</div>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"execution_count": 13
|
|
}
|
|
],
|
|
"metadata": {}
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"source": [
|
|
"For dis dataset, di columns be like dis: \n",
|
|
"* Age and sex na easy to understand \n",
|
|
"* BMI na body mass index \n",
|
|
"* BP na di average blood pressure \n",
|
|
"* S1 to S6 na different blood measurements \n",
|
|
"* Y na di qualitative measure of how di disease don waka for one year \n",
|
|
"\n",
|
|
"Make we study dis dataset wit methods wey concern probability and statistics.\n",
|
|
"\n",
|
|
"### Task 1: Calculate di mean values and variance for all di values\n"
|
|
],
|
|
"metadata": {}
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"source": [],
|
|
"outputs": [],
|
|
"metadata": {}
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"source": [
|
|
"### Task 2: Draw boxplot for BMI, BP and Y based on gender\n"
|
|
],
|
|
"metadata": {}
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"source": [],
|
|
"outputs": [],
|
|
"metadata": {}
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"source": [
|
|
"### Task 3: Wetin be di distribution of Age, Sex, BMI and Y variables?\n"
|
|
],
|
|
"metadata": {}
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"source": [],
|
|
"outputs": [],
|
|
"metadata": {}
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"source": [
|
|
"### Task 4: Test di correlation wey dey between different variables and how disease dey progress (Y)\n",
|
|
"\n",
|
|
"> **Hint** Correlation matrix go show you di most useful info wey go help you know which values dey depend on each oda.\n"
|
|
],
|
|
"metadata": {}
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"source": [],
|
|
"metadata": {}
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"source": [
|
|
"### Task 5: Test di hypothesis say di degree of diabetes progression dey different between men and women\n"
|
|
],
|
|
"metadata": {}
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"source": [],
|
|
"metadata": {}
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"---\n\n<!-- CO-OP TRANSLATOR DISCLAIMER START -->\n**Disclaimer**: \nDis dokyument don translate wit AI translation service [Co-op Translator](https://github.com/Azure/co-op-translator). Even as we dey try make am correct, abeg sabi say machine translation fit get mistake or no dey accurate well. Di original dokyument for im native language na di main source wey you go trust. For important information, e better make professional human translator check am. We no go fit take blame for any misunderstanding or wrong interpretation wey fit happen because you use dis translation.\n<!-- CO-OP TRANSLATOR DISCLAIMER END -->\n"
|
|
]
|
|
}
|
|
],
|
|
"metadata": {
|
|
"orig_nbformat": 4,
|
|
"language_info": {
|
|
"name": "python",
|
|
"version": "3.8.8",
|
|
"mimetype": "text/x-python",
|
|
"codemirror_mode": {
|
|
"name": "ipython",
|
|
"version": 3
|
|
},
|
|
"pygments_lexer": "ipython3",
|
|
"nbconvert_exporter": "python",
|
|
"file_extension": ".py"
|
|
},
|
|
"kernelspec": {
|
|
"name": "python3",
|
|
"display_name": "Python 3.8.8 64-bit (conda)"
|
|
},
|
|
"interpreter": {
|
|
"hash": "86193a1ab0ba47eac1c69c1756090baa3b420b3eea7d4aafab8b85f8b312f0c5"
|
|
},
|
|
"coopTranslator": {
|
|
"original_hash": "6d945fd15163f60cb473dbfe04b2d100",
|
|
"translation_date": "2025-11-18T19:10:24+00:00",
|
|
"source_file": "1-Introduction/04-stats-and-probability/assignment.ipynb",
|
|
"language_code": "pcm"
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 2
|
|
} |