{
"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": {}
}
]
}