Central limit theorem.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "b0757183",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy.random as np\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "population_size = 1000000\n",
    "population = np.rand(population_size)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "0850dbf4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1000000 [0.42500426 0.02006059 0.77454089 ... 0.27219633 0.32400268 0.18100194]\n"
     ]
    }
   ],
   "source": [
    "print(len(population),population)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "d57b4305",
   "metadata": {},
   "outputs": [],
   "source": [
    "number_of_samples = 10000\n",
    "sample_means = np.rand(number_of_samples)\n",
    "sample_size = 10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "fc6d3085",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.89181579, 0.7478453 , 0.67101059, ..., 0.91665594, 0.7380018 ,\n",
       "       0.05238412])"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sample_means"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "3c1268e7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10000 [0.09051854 0.1506807  0.32457068 ... 0.4186492  0.99758789 0.39485906]\n"
     ]
    }
   ],
   "source": [
    "c = np.rand(number_of_samples)\n",
    "print(len(c),c)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "be66d079",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10 [754859 115854 315608 565136 962952 119158 877036 111426 636268 200445]\n",
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    {
     "name": "stdout",
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    {
     "name": "stdout",
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    {
     "name": "stdout",
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      "10 [661403 146752 731619 428796 996669 445170 318589  39226 160219 792686]\n",
      "10 [609761 663312 414994 851925 322647 464545 192804 498457 347396 706301]\n",
      "10 [682529 320971 488709 819788 117677 685910  54139 554179 129292 785099]\n",
      "10 [120154  40775 810389 674608 323784 748231 893851 893229 929447 526587]\n",
      "10 [750810 824072 609434 983915 664684 982418 727207 948701 195015 594117]\n",
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      "10 [248297 707877 720468 940599  28752 273761 593882 659594  71120 571286]\n",
      "10 [749014 242776 791435 308336 276866 916430 696419 697911 953689 258081]\n",
      "10 [146271 579006 945495 956116 908795 575751 494337 838417 551167 635814]\n",
      "10 [337134 545224 190164 357930 938342 397208 716205 921504 123716 991189]\n",
      "10 [657123 994222 433258 194134 921007 347393 956073 789927 108938 624995]\n",
      "10 [352941 358422 257182 330863 173993 819184 205158 419949 563940 255081]\n",
      "10 [835702 275666 584420 137675  84873 380539 673040 650877 418761 441945]\n"
     ]
    }
   ],
   "source": [
    "for i in range(0,number_of_samples):\n",
    "    c = np.randint(1,population_size,sample_size)\n",
    "    print(len(c),c)\n",
    "    sample_means[i] = population[c].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "bb918a6b",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Suresh\\AppData\\Local\\Temp\\ipykernel_11868\\1953955786.py:4: UserWarning: \n",
      "\n",
      "`distplot` is a deprecated function and will be removed in seaborn v0.14.0.\n",
      "\n",
      "Please adapt your code to use either `displot` (a figure-level function with\n",
      "similar flexibility) or `histplot` (an axes-level function for histograms).\n",
      "\n",
      "For a guide to updating your code to use the new functions, please see\n",
      "https://gist.github.com/mwaskom/de44147ed2974457ad6372750bbe5751\n",
      "\n",
      "  sns.distplot(sample_means,bins = int(180/5), hist = True, kde = False)\n",
      "C:\\Users\\Suresh\\AppData\\Local\\Temp\\ipykernel_11868\\1953955786.py:11: UserWarning: \n",
      "\n",
      "`distplot` is a deprecated function and will be removed in seaborn v0.14.0.\n",
      "\n",
      "Please adapt your code to use either `displot` (a figure-level function with\n",
      "similar flexibility) or `kdeplot` (an axes-level function for kernel density plots).\n",
      "\n",
      "For a guide to updating your code to use the new functions, please see\n",
      "https://gist.github.com/mwaskom/de44147ed2974457ad6372750bbe5751\n",
      "\n",
      "  sns.distplot(sample_means,hist = False,kde = True)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.subplot(1,2,1)\n",
    "plt.xticks(fontsize = 14)\n",
    "plt.yticks(fontsize = 14)\n",
    "sns.distplot(sample_means,bins = int(180/5), hist = True, kde = False)\n",
    "plt.title(\"Histogram of Sample means\",fontsize= 20)\n",
    "plt.xlabel(\"Sample mean\",fontsize = 20)\n",
    "plt.ylabel(\"Count\",fontsize = 20)\n",
    "plt.subplot(1,2,2)\n",
    "plt.xticks(fontsize = 14)\n",
    "plt.yticks(fontsize = 14)\n",
    "sns.distplot(sample_means,hist = False,kde = True)\n",
    "plt.title(\"Density of Sample means \",fontsize = 20)\n",
    "plt.xlabel(\"Sample mean\",fontsize = 20)\n",
    "plt.ylabel(\"Density\",fontsize = 20)\n",
    "plt.subplots_adjust(bottom= 0.1,right = 2,top = 0.9)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1682e87e",
   "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": "3.10.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}