s444409/Bootstrap-t-student
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s444501 2022-05-13 22:06:56 +02:00
parent 7e0cf14302
commit 642ba2b80a
1 changed files with 49 additions and 10 deletions
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bootstrap-t.ipynb
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@ -1,8 +1,31 @@
{
"cells": [
{
"cell_type": "markdown",
"source": [
"Bootstrapowa wersja testu t.\n",
"Implementacja powinna obejmować test dla jednej próby, dla dwóch prób niezależnych oraz dla dwóch prób zależnych.\n",
"W każdej sytuacji oczekiwanym wejście jest zbiór danych w odpowiednim formacie, a wyjściem p-wartość oraz ostateczna decyzja.\n",
"Dodatkowo powinien być rysowany odpowiedni rozkład statystyki testowej."
],
"metadata": {
"collapsed": false
}
},
{
"cell_type": "markdown",
"source": [
"Zbiór danych - ???\n",
"Hipoteza zerowa - ???\n",
"Hipoteza alternatywna - ???"
],
"metadata": {
"collapsed": false
}
},
{
"cell_type": "code",
"execution_count": 46,
"execution_count": 50,
"metadata": {
"pycharm": {
"name": "#%%\n"
@ -19,7 +42,7 @@
},
{
"cell_type": "code",
"execution_count": 47,
"execution_count": 51,
"metadata": {
"pycharm": {
"name": "#%%\n"
@ -29,14 +52,14 @@
"source": [
"def generate_bootstraps(data, n_bootstraps=100):\n",
" data_size = data.shape[0]\n",
" for b in range(n_bootstraps):\n",
" indicies = np.random.choice(len(data), size=data_size)\n",
" yield data.iloc[indicies, :]"
" for _ in range(n_bootstraps):\n",
" indices = np.random.choice(len(data), size=data_size)\n",
" yield data.iloc[indices, :]"
]
},
{
"cell_type": "code",
"execution_count": 48,
"execution_count": 52,
"outputs": [],
"source": [
"def get_t_stat(data1, data2):\n",
@ -57,7 +80,7 @@
},
{
"cell_type": "code",
"execution_count": 49,
"execution_count": 53,
"metadata": {
"pycharm": {
"name": "#%%\n"
@ -80,7 +103,7 @@
},
{
"cell_type": "code",
"execution_count": 50,
"execution_count": 54,
"outputs": [],
"source": [
"def make_decision(data, columns, alpha=0.05):\n",
@ -104,13 +127,29 @@
},
{
"cell_type": "code",
"execution_count": 51,
"execution_count": 55,
"outputs": [],
"source": [
"def draw_distribution():\n",
" \"\"\"Funkcja rysuje rozkład statystyki testowej\"\"\"\n",
" pass"
],
"metadata": {
"collapsed": false,
"pycharm": {
"name": "#%%\n"
}
}
},
{
"cell_type": "code",
"execution_count": 56,
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"t: 6.903407918031469, df: 998, cv: 1.6463818766348755, p: 9.018563673635072e-12\n",
"t: 6.891235313595221, df: 998, cv: 1.6463818766348755, p: 9.78683800667568e-12\n",
"\n",
"Reject the null hypothesis that the means are equal.\n",
"Reject the null hypothesis that the means are equal.\n"