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262 lines
7.4 KiB
262 lines
7.4 KiB
{
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"cells": [
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{
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"cell_type": "markdown",
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"source": [
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"## Įvadas į tikimybes ir statistiką\n",
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"## Užduotis\n",
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"\n",
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"Šioje užduotyje naudosime diabetu sergančių pacientų duomenų rinkinį, paimtą [iš čia](https://www4.stat.ncsu.edu/~boos/var.select/diabetes.html).\n"
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],
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"metadata": {}
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},
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{
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"cell_type": "code",
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"execution_count": 13,
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"source": [
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"import pandas as pd\r\n",
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"import numpy as np\r\n",
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"\r\n",
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"df = pd.read_csv(\"../../data/diabetes.tsv\",sep='\\t')\r\n",
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"df.head()"
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],
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"outputs": [
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{
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"output_type": "execute_result",
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"data": {
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"text/plain": [
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" AGE SEX BMI BP S1 S2 S3 S4 S5 S6 Y\n",
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"0 59 2 32.1 101.0 157 93.2 38.0 4.0 4.8598 87 151\n",
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"1 48 1 21.6 87.0 183 103.2 70.0 3.0 3.8918 69 75\n",
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"2 72 2 30.5 93.0 156 93.6 41.0 4.0 4.6728 85 141\n",
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"3 24 1 25.3 84.0 198 131.4 40.0 5.0 4.8903 89 206\n",
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"4 50 1 23.0 101.0 192 125.4 52.0 4.0 4.2905 80 135"
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],
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"text/html": [
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"<div>\n",
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"<style scoped>\n",
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" .dataframe tbody tr th:only-of-type {\n",
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" vertical-align: middle;\n",
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" }\n",
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"\n",
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" .dataframe tbody tr th {\n",
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" vertical-align: top;\n",
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" }\n",
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"\n",
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" .dataframe thead th {\n",
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" text-align: right;\n",
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" }\n",
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"</style>\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>AGE</th>\n",
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" <th>SEX</th>\n",
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" <th>BMI</th>\n",
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" <th>BP</th>\n",
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" <th>S1</th>\n",
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" <th>S2</th>\n",
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" <th>S3</th>\n",
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" <th>S4</th>\n",
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" <th>S5</th>\n",
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" <th>S6</th>\n",
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" <th>Y</th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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" <th>0</th>\n",
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" <td>59</td>\n",
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" <td>2</td>\n",
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" <td>32.1</td>\n",
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" <td>101.0</td>\n",
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" <td>157</td>\n",
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" <td>93.2</td>\n",
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" <td>38.0</td>\n",
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" <td>4.0</td>\n",
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" <td>4.8598</td>\n",
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" <td>87</td>\n",
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" <td>151</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>1</th>\n",
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" <td>48</td>\n",
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" <td>1</td>\n",
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" <td>21.6</td>\n",
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" <td>87.0</td>\n",
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" <td>183</td>\n",
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" <td>103.2</td>\n",
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" <td>70.0</td>\n",
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" <td>3.0</td>\n",
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" <td>3.8918</td>\n",
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" <td>69</td>\n",
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" <td>75</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>2</th>\n",
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" <td>72</td>\n",
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" <td>2</td>\n",
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" <td>30.5</td>\n",
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" <td>93.0</td>\n",
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" <td>156</td>\n",
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" <td>93.6</td>\n",
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" <td>41.0</td>\n",
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" <td>4.0</td>\n",
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" <td>4.6728</td>\n",
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" <td>85</td>\n",
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" <td>141</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>3</th>\n",
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" <td>24</td>\n",
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" <td>1</td>\n",
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" <td>25.3</td>\n",
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" <td>84.0</td>\n",
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" <td>198</td>\n",
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" <td>131.4</td>\n",
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" <td>40.0</td>\n",
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" <td>5.0</td>\n",
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" <td>4.8903</td>\n",
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" <td>89</td>\n",
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" <td>206</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>4</th>\n",
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" <td>50</td>\n",
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" <td>1</td>\n",
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" <td>23.0</td>\n",
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" <td>101.0</td>\n",
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" <td>192</td>\n",
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" <td>125.4</td>\n",
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" <td>52.0</td>\n",
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" <td>4.0</td>\n",
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" <td>4.2905</td>\n",
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" <td>80</td>\n",
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" <td>135</td>\n",
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" </tr>\n",
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" </tbody>\n",
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"</table>\n",
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"</div>"
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]
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},
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"metadata": {},
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"execution_count": 13
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}
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],
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"metadata": {}
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},
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{
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"cell_type": "markdown",
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"source": [
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"Šiame duomenų rinkinyje stulpeliai yra tokie: \n",
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"* Amžius ir lytis yra savaime suprantami \n",
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"* KMI yra kūno masės indeksas \n",
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"* AKS yra vidutinis kraujo spaudimas \n",
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"* S1 iki S6 yra skirtingi kraujo matavimai \n",
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"* Y yra kokybinis ligos progresavimo matas per vienerius metus \n",
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"\n",
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"Išnagrinėkime šį duomenų rinkinį naudodami tikimybių ir statistikos metodus.\n",
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"\n",
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"### Užduotis 1: Apskaičiuokite visų reikšmių vidurkius ir dispersijas\n"
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],
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"metadata": {}
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"source": [],
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"outputs": [],
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"metadata": {}
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},
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{
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"cell_type": "markdown",
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"source": [
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"### Užduotis 2: Nubraižykite dėžės diagramas BMI, BP ir Y priklausomai nuo lyties\n"
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],
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"metadata": {}
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"source": [],
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"outputs": [],
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"metadata": {}
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},
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{
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"cell_type": "markdown",
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"source": [
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"### Užduotis 3: Koks yra amžiaus, lyties, KMI ir Y kintamųjų pasiskirstymas?\n"
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],
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"metadata": {}
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"source": [],
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"outputs": [],
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"metadata": {}
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},
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{
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"cell_type": "markdown",
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"source": [
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"### Užduotis 4: Patikrinti koreliaciją tarp skirtingų kintamųjų ir ligos progresavimo (Y)\n",
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"\n",
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"> **Patarimas** Koreliacijos matrica suteiks naudingiausią informaciją apie tai, kurie rodikliai yra priklausomi.\n"
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],
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"metadata": {}
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"\n---\n\n**Atsakomybės apribojimas**: \nŠis dokumentas buvo išverstas naudojant AI vertimo paslaugą [Co-op Translator](https://github.com/Azure/co-op-translator). Nors siekiame tikslumo, prašome atkreipti dėmesį, kad automatiniai vertimai gali turėti klaidų ar netikslumų. Originalus dokumentas jo gimtąja kalba turėtų būti laikomas autoritetingu šaltiniu. Kritinei informacijai rekomenduojama profesionali žmogaus vertimo paslauga. Mes neprisiimame atsakomybės už nesusipratimus ar klaidingus interpretavimus, atsiradusius dėl šio vertimo naudojimo.\n"
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]
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}
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