{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "### Drawing cards\n", "\n", "NOTE: In this notebook I use the `stats` sub-module of `scipy` for all statistics functions, including generation of random numbers. There are other modules with some overlapping functionality, e.g., the regular python random module, and the `scipy.random` module, but I do not use them here. The `stats` sub-module includes tools for a large number of distributions, it includes a large and growing set of statistical functions, and there is a unified class structure. (And namespace issues are minimized.) See https://docs.scipy.org/doc/scipy/reference/stats.html." ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "from scipy import stats" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Intro\n", "\n", "For each of the draws, the probability of getting a heart is $\\frac{1}{4}$. The probability of getting $k$ successes in $n$ independent trials, where the $p$ is the probability of success in an indvidual trial is given by the binomial distribution `stats.binom.pmf(k,n,p)`:" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "The probability of 0 hearts is 0.17797851562499994\n", "The probability of 1 hearts is 0.35595703125\n", "The probability of 2 hearts is 0.296630859375\n", "The probability of 3 hearts is 0.13183593749999992\n", "The probability of 4 hearts is 0.03295898437499997\n", "The probability of 5 hearts is 0.004394531250000001\n", "The probability of 6 hearts is 0.000244140625\n" ] } ], "source": [ "for k in range(7):\n", " n = 6\n", " p = 0.25\n", " print(\"The probability of\",k,\"hearts is\", stats.binom.pmf(k,n,p))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Version information\n", "`version_information` is from J.R. Johansson (jrjohansson at gmail.com); see Introduction to scientific computing with Python for more information and instructions for package installation.\n" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "%load_ext version_information" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "application/json": { "Software versions": [ { "module": "Python", "version": "3.11.5 64bit [MSC v.1916 64 bit (AMD64)]" }, { "module": "IPython", "version": "8.15.0" }, { "module": "OS", "version": "Windows 10 10.0.26100 SP0" }, { "module": "scipy", "version": "1.11.1" }, { "module": "matplotlib", "version": "3.7.2" } ] }, "text/html": [ "
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scipy1.11.1
matplotlib3.7.2
Sat Feb 08 14:44:35 2025 Eastern Standard Time
" ], "text/latex": [ "\\begin{tabular}{|l|l|}\\hline\n", "{\\bf Software} & {\\bf Version} \\\\ \\hline\\hline\n", "Python & 3.11.5 64bit [MSC v.1916 64 bit (AMD64)] \\\\ \\hline\n", "IPython & 8.15.0 \\\\ \\hline\n", "OS & Windows 10 10.0.26100 SP0 \\\\ \\hline\n", "scipy & 1.11.1 \\\\ \\hline\n", "matplotlib & 3.7.2 \\\\ \\hline\n", "\\hline \\multicolumn{2}{|l|}{Sat Feb 08 14:44:35 2025 Eastern Standard Time} \\\\ \\hline\n", "\\end{tabular}\n" ], "text/plain": [ "Software versions\n", "Python 3.11.5 64bit [MSC v.1916 64 bit (AMD64)]\n", "IPython 8.15.0\n", "OS Windows 10 10.0.26100 SP0\n", "scipy 1.11.1\n", "matplotlib 3.7.2\n", "Sat Feb 08 14:44:35 2025 Eastern Standard Time" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "version_information scipy, matplotlib" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "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": "3.11.5" } }, "nbformat": 4, "nbformat_minor": 4 }