{ "cells": [ { "cell_type": "markdown", "id": "486faa34", "metadata": {}, "source": [ "https://towardsdatascience.com/anova-test-with-python-cfbf4013328b" ] }, { "cell_type": "code", "execution_count": null, "id": "0a5cc6a3", "metadata": {}, "outputs": [], "source": [ "import pandas as pd\n", "import random\n", "\n", "# read original dataset\n", "student_df = pd.read_csv('students.csv')" ] }, { "cell_type": "code", "execution_count": 1, "id": "1c9bf355", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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majorsalary
0Biology87
1Economics and Finance94
2Environmental Sciences97
3Mathematics and Statistics75
4Political Science84
5Social Sciences63
\n", "
" ], "text/plain": [ " major salary\n", "0 Biology 87\n", "1 Economics and Finance 94\n", "2 Environmental Sciences 97\n", "3 Mathematics and Statistics 75\n", "4 Political Science 84\n", "5 Social Sciences 63" ] }, "execution_count": 1, "metadata": {}, "output_type": "execute_result" } ], "source": [ "\n", "\n", "\n", "# filter the students who are graduated\n", "graduated_student_df = student_df[student_df['graduated'] == 1]\n", "\n", "# random sample for 500 students \n", "unique_student_id = list(graduated_student_df['stud.id'].unique())\n", "random.seed(30) # set a seed so that everytime we will extract same sample\n", "sample_student_id = random.sample(unique_student_id, 500)\n", "sample_df = graduated_student_df[graduated_student_df['stud.id'].isin(sample_student_id)].reset_index(drop=True)\n", "\n" ] }, { "cell_type": "code", "execution_count": null, "id": "8b99103b", "metadata": {}, "outputs": [], "source": [ "# two variables of interest\n", "sample_df = sample_df[['major', 'salary']]\n", "groups = sample_df.groupby('major').count().reset_index()\n", "# groups.plot(kind='bar',x='major',y='salary')\n", "groups" ] }, { "cell_type": "code", "execution_count": 2, "id": "bd48c0b6", "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "## Normality check\n", "\n", "import numpy as np \n", "import scipy.stats as stats\n", "import matplotlib.pyplot as plt\n", "\n", "unique_majors = sample_df['major'].unique()\n", "for major in unique_majors:\n", " stats.probplot(sample_df[sample_df['major'] == major]['salary'], dist=\"norm\", plot=plt)\n", " plt.title(\"Probability Plot - \" + major)\n", " plt.show()" ] }, { "cell_type": "code", "execution_count": 3, "id": "6eabda03", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "salary 1.669921\n", "dtype: float64" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Homogeneity of variance Assumption Check\n", "# calculate ratio of the largest to the smallest sample standard deviation\n", "ratio = sample_df.groupby('major').std().max() / sample_df.groupby('major').std().min()\n", "ratio" ] }, { "cell_type": "markdown", "id": "7010a867", "metadata": {}, "source": [ "The ratio of the largest to the smallest sample standard deviation is 1.67. That is less than the threshold of 2. \n", "Thus, we conclude that the assumptions are fulfilled." ] }, { "cell_type": "code", "execution_count": 4, "id": "f34016e2", "metadata": { "scrolled": true }, "outputs": [ { "data": { "text/html": [ "
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SSdfMSFP-valueF crit
Source of Variation
Between Groups24184075535.07410454836815107.01482177.4080370.02.592178
Within Groups30867423591.21926949462484663.14012
Total55051499126.293373499110323645.543674
\n", "
" ], "text/plain": [ " SS df MS F \\\n", "Source of Variation \n", "Between Groups 24184075535.074104 5 4836815107.014821 77.408037 \n", "Within Groups 30867423591.219269 494 62484663.14012 \n", "Total 55051499126.293373 499 110323645.543674 \n", "\n", " P-value F crit \n", "Source of Variation \n", "Between Groups 0.0 2.592178 \n", "Within Groups \n", "Total " ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Create ANOVA backbone table\n", "data = [['Between Groups', '', '', '', '', '', ''], ['Within Groups', '', '', '', '', '', ''], ['Total', '', '', '', '', '', '']] \n", "anova_table = pd.DataFrame(data, columns = ['Source of Variation', 'SS', 'df', 'MS', 'F', 'P-value', 'F crit']) \n", "anova_table.set_index('Source of Variation', inplace = True)\n", "\n", "# calculate SSTR and update anova table\n", "x_bar = sample_df['salary'].mean()\n", "SSTR = sample_df.groupby('major').count() * (sample_df.groupby('major').mean() - x_bar)**2\n", "anova_table['SS']['Between Groups'] = SSTR['salary'].sum()\n", "\n", "# calculate SSE and update anova table\n", "SSE = (sample_df.groupby('major').count() - 1) * sample_df.groupby('major').std()**2\n", "anova_table['SS']['Within Groups'] = SSE['salary'].sum()\n", "\n", "# calculate SSTR and update anova table\n", "SSTR = SSTR['salary'].sum() + SSE['salary'].sum()\n", "anova_table['SS']['Total'] = SSTR\n", "\n", "# update degree of freedom\n", "anova_table['df']['Between Groups'] = sample_df['major'].nunique() - 1\n", "anova_table['df']['Within Groups'] = sample_df.shape[0] - sample_df['major'].nunique()\n", "anova_table['df']['Total'] = sample_df.shape[0] - 1\n", "\n", "# calculate MS\n", "anova_table['MS'] = anova_table['SS'] / anova_table['df']\n", "\n", "# calculate F \n", "F = anova_table['MS']['Between Groups'] / anova_table['MS']['Within Groups']\n", "anova_table['F']['Between Groups'] = F\n", "\n", "# p-value\n", "anova_table['P-value']['Between Groups'] = 1 - stats.f.cdf(F, anova_table['df']['Between Groups'], anova_table['df']['Within Groups'])\n", "\n", "# F critical \n", "alpha = 0.05\n", "# possible types \"right-tailed, left-tailed, two-tailed\"\n", "tail_hypothesis_type = \"two-tailed\"\n", "if tail_hypothesis_type == \"two-tailed\":\n", " alpha /= 2\n", "anova_table['F crit']['Between Groups'] = stats.f.ppf(1-alpha, anova_table['df']['Between Groups'], anova_table['df']['Within Groups'])\n", "\n", "# Final ANOVA Table\n", "anova_table" ] }, { "cell_type": "code", "execution_count": 5, "id": "5344ce6f", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Approach 1: The p-value approach to hypothesis testing in the decision rule\n", "F-score is: 77.40803685167364 and p value is: 1.1102230246251565e-16\n", "Null Hypothesis is rejected.\n", "\n", "--------------------------------------------------------------------------------------\n", "Approach 2: The critical value approach to hypothesis testing in the decision rule\n", "F-score is: 77.40803685167364 and critical value is: 2.592178494905\n", "Null Hypothesis is rejected.\n" ] } ], "source": [ "# The p-value approach\n", "print(\"Approach 1: The p-value approach to hypothesis testing in the decision rule\")\n", "conclusion = \"Failed to reject the null hypothesis.\"\n", "if anova_table['P-value']['Between Groups'] <= alpha:\n", " conclusion = \"Null Hypothesis is rejected.\"\n", "print(\"F-score is:\", anova_table['F']['Between Groups'], \" and p value is:\", anova_table['P-value']['Between Groups']) \n", "print(conclusion)\n", " \n", "# The critical value approach\n", "print(\"\\n--------------------------------------------------------------------------------------\")\n", "print(\"Approach 2: The critical value approach to hypothesis testing in the decision rule\")\n", "conclusion = \"Failed to reject the null hypothesis.\"\n", "if anova_table['F']['Between Groups'] > anova_table['F crit']['Between Groups']:\n", " conclusion = \"Null Hypothesis is rejected.\"\n", "print(\"F-score is:\", anova_table['F']['Between Groups'], \" and critical value is:\", anova_table['F crit']['Between Groups'])\n", "print(conclusion)" ] }, { "cell_type": "code", "execution_count": null, "id": "0b13abe5", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "id": "4d849842", "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "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": "3.8.8" } }, "nbformat": 4, "nbformat_minor": 5 }