edited snippit

Author: chrisalbon

kolmogorov_smirnov_test.ipynb

@@ -0,0 +1,128 @@
+{
+ "metadata": {
+  "name": "",
+  "signature": "sha256:e09ae16e2934781defa7f6b97ad14295518732fccc8478f9854e4ea31013324d"
+ },
+ "nbformat": 3,
+ "nbformat_minor": 0,
+ "worksheets": [
+  {
+   "cells": [
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "# Import required packages\n",
+      "from scipy import stats\n",
+      "import scipy as sp\n",
+      "import numpy as np\n",
+      "import math\n",
+      "import matplotlib.pyplot as plt\n",
+      "%matplotlib inline"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [],
+     "prompt_number": 9
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "# Create x, which is uniformly distributed\n",
+      "x = np.random.uniform(size=1000)\n",
+      "\n",
+      "# Plot x to double check its distribution\n",
+      "plt.hist(x)\n",
+      "plt.show()"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [
+      {
+       "metadata": {},
+       "output_type": "display_data",
+       "png": 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2V1UlCcfqyclHN0pbbASexdIpyScBn03yuaq6f10rm75R2uLtwF1VNZfkScB8kmdU1XfW\nubZZtKbcXK+QH+WiqJXbbOnWtWakC8S6f7ZeBWytqtX+XDuWjdIWzwY+spTvnAr8QpLFqrpxOiVO\nzShtsR/4WlV9F/hukn8CngG0FvKjtMULgD8EqKovJ/kP4CnA7VOpcHasOTfXa7jmduDJSc5KciLw\ncmDlh/RG4NcBkjwP+GZVLaxTPUM6alsk+QngeuBVVfXAADVOy1Hboqp+sqrOrqqzWRqX/+0GAx5G\n+4z8HfAzSU5IchJL/2jbPeU6p2GUttgDXADQjUE/Bfj3qVY5G9acm+vSk6/HuSgqyW92j3+wqm5O\ncmGSB4D/AV67HrUMbZS2AN4B/Djwga4Hu1hV5w9V83oZsS2OCyN+RvYk+QTwReBR4Kqqai7kR3xf\nvAu4JsndLHVOf7+qvj5Y0eskybXAi4FTk+wHrmBp2K53bnoxlCQ1zK//k6SGGfKS1DBDXpIaZshL\nUsMMeUlqmCEvSQ0z5CWpYYa8JDXs/wCLB9KBBH4/dgAAAABJRU5ErkJggg==\n",
+       "text": [
+        "<matplotlib.figure.Figure at 0x107bba690>"
+       ]
+      }
+     ],
+     "prompt_number": 10
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "# Create x, which is NOT uniformly distributed\n",
+      "y = x**4\n",
+      "\n",
+      "# Plot x to double check its distribution\n",
+      "plt.hist(y)\n",
+      "plt.show()"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [
+      {
+       "metadata": {},
+       "output_type": "display_data",
+       "png": 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+       "text": [
+        "<matplotlib.figure.Figure at 0x107af6d50>"
+       ]
+      }
+     ],
+     "prompt_number": 11
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "# Run kstest on x. We want the second returned value to be \n",
+      "# not statistically significant, meaning that both come from \n",
+      "# the same distribution.\n",
+      "stats.kstest(x, 'uniform', args=(min(x),max(x)))"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [
+      {
+       "metadata": {},
+       "output_type": "pyout",
+       "prompt_number": 12,
+       "text": [
+        "(0.026995716660981411, 0.45735224284132037)"
+       ]
+      }
+     ],
+     "prompt_number": 12
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "# Run kstest on y. We want the second returned value to be \n",
+      "# statistically significant, meaning that likely do not both \n",
+      "# come from the same distribution.\n",
+      "stats.kstest(y, 'uniform', args=(min(y),max(y)))"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [
+      {
+       "metadata": {},
+       "output_type": "pyout",
+       "prompt_number": 13,
+       "text": [
+        "(0.47537839506450752, 0.0)"
+       ]
+      }
+     ],
+     "prompt_number": 13
+    }
+   ],
+   "metadata": {}
+  }
+ ]
+}