{ "metadata": { "name": "" }, "nbformat": 3, "nbformat_minor": 0, "worksheets": [ { "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Distribution binomiale\n", "\n", "Il y a beaucoup de vid\u00e9os sur le [site de l'Acad\u00e9mie Khan](https://fr.khanacademy.org/) qui concernent la distribution binomiale. Je n'ai pas envie de r\u00e9viser autant de combinatoire de base, mais il y en a qui m'int\u00e9ressent.\n", "\n", "## L'esp\u00e8rance d'une distribution binomiale\n", "\n", "J'avais du mal avec ce sujet quand j'\u00e9tudias la distribution Poisson." ] }, { "cell_type": "code", "collapsed": false, "input": [ "from IPython.display import YouTubeVideo\n", "YouTubeVideo(\"sSLhCvlZN1w\")" ], "language": "python", "metadata": {}, "outputs": [ { "html": [ "\n", " \n", " " ], "metadata": {}, "output_type": "pyout", "prompt_number": 1, "text": [ "" ] } ], "prompt_number": 1 }, { "cell_type": "markdown", "metadata": {}, "source": [ "La loi binomiale. Oui, elle est \u00e9vidente avec un peu de combinatoire.\n", "\n", "$$P(X=k) = {n \\choose k}p^k(1 - p)^{n-k}$$\n", "\n", "Et l'esp\u00e8rance, ou la valeur pr\u00e9vue :\n", "\n", "$$\\begin{aligned}\n", "E(X) &= \\sum_{k=0}^{n} k{n \\choose k} p^k (1-p)^{n-k} \\\\\n", " &= \\sum_{k=1}^{n} k{n \\choose k} p^k (1-p)^{n-k} \\quad &\\text{pas de terme quand }k=0 \\\\\n", " &= \\sum_{k=1}^{n} k\\frac{n!}{(n-k)!k!} p^k (1-p)^{n-k} \\\\\n", " &= np \\sum_{k=1}^{n} \\frac{(n-1)!}{(n-k)!(k-1)!} p^{k-1} (1-p)^{n-k} \\\\\n", " &= np \\sum_{a=0}^{b} \\frac{b!}{(b-a)!a!} p^a (1-p)^{b-a} \\quad &\\text{soit }a=k-1\\text{ et }b=n-1 \\\\\n", " &= np \\sum_{a=0}^{b} {b \\choose a} p^a (1-p)^{b-a} \\\\\n", " &= np\n", "\\end{aligned}$$" ] } ], "metadata": {} } ] }