Basic_statistics_2.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "791b338e",
   "metadata": {},
   "source": [
    "# SET-1(Descriptive Statistics and Probability)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "2da5697d",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import scipy \n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "\n",
    "from scipy import stats\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a867251e",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "82164711",
   "metadata": {},
   "outputs": [],
   "source": [
    "A=pd.Series([24.23,25.53,25.41,24.14,29.62,28.25,25.81,24.39,40.26,32.95,91.36,25.99,39.42,26.71,35.00])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "2c528e9d",
   "metadata": {},
   "outputs": [],
   "source": [
    "name=[\"Allied Signal\",\"Bankers Trust\",\"General Mills\",\"ITT Industries\",\"J.P.Morgan & Co.\",\"Lehman Brothers\",\"Marriott\",\n",
    "\"MCI\",\"Merrill Lynch\",\"Microsoft\",\"Morgan Stanley\",\"Sun Microsystems\",\"Travelers\",\"US Airways\",\"Warner-Lambert\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "0285827b",
   "metadata": {},
   "outputs": [],
   "source": [
    "sns.boxplot?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "id": "faeae195",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.pie(A,labels=name)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "id": "f15b0c35",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    15.000000\n",
       "mean     33.271333\n",
       "std      16.945401\n",
       "min      24.140000\n",
       "25%      25.470000\n",
       "50%      26.710000\n",
       "75%      33.975000\n",
       "max      91.360000\n",
       "dtype: float64"
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "A.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "id": "70748656",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "287.1466123809524"
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "A.var()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "id": "0b59728f",
   "metadata": {},
   "outputs": [],
   "source": [
    "C=  [(-2000*0.1)+(-1000*0.1)+(0)+(1000*0.2)+( 2000*0.3)+( 3000*0.1)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "id": "141a78a1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[800.0]"
      ]
     },
     "execution_count": 105,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "C"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ee252c58",
   "metadata": {},
   "source": [
    "# SET - 02"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "id": "892d1e55",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.26598552904870054"
      ]
     },
     "execution_count": 109,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Q no.01\n",
    "1-stats.norm.cdf(50,45,8)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "id": "75cafb5c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "the NO of employees at age more than 44: 63 0\n",
      "the NO of employees at  age between 38 and 44: 137 0\n"
     ]
    }
   ],
   "source": [
    "#q no.02\n",
    "print(\"the NO of employees at age more than 44:\",round(((1-stats.norm.cdf(44,38,6))*400)),0)\n",
    "print(\"the NO of employees at  age between 38 and 44:\",round((stats.norm.cdf(44,38,6)-stats.norm.cdf(38,38,6))*400),0)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "id": "b9680e27",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "No of employees at or below age 30 : 36.0\n"
     ]
    }
   ],
   "source": [
    "print(\"No of employees at or below age 30 :\",round((stats.norm.cdf(30,38,6))*400,0))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "id": "3b745746",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(48.48341392902199, 151.516586070978)"
      ]
     },
     "execution_count": 127,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#q no 4\n",
    "stats.norm.interval(0.99,100,20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "id": "7e286707",
   "metadata": {},
   "outputs": [],
   "source": [
    "#q no 5\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "id": "576aa1d0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The mean of the two profit is: 540 Million Rupees\n",
      "the sum of the two profits standard deviation is : 225 Million Rupees\n"
     ]
    }
   ],
   "source": [
    "# sum of mean from the two profits = 5+7,\n",
    "mean= 12\n",
    "print(\"The mean of the two profit is:\",mean*45,\"Million Rupees\")\n",
    "# sum of the standard deviation of two profits is S.D= sqrt(9+16) = 5\n",
    "SD=5\n",
    "print(\"the sum of the two profits standard deviation is :\",SD*45,\"Million Rupees\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "id": "630a30ca",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The rupee range that contains 95% of annual probability is: (99.00810347848784, 980.9918965215122) Million rupees\n"
     ]
    }
   ],
   "source": [
    "print(\"The rupee range that contains 95% of annual probability is:\",stats.norm.interval(.95,540,225),\"Million rupees\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 148,
   "id": "ecfb2bc2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-1.6448536269514729"
      ]
     },
     "execution_count": 148,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 5th percentile profit\n",
    "stats.norm.ppf(.05)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 150,
   "id": "9c092eb9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The probability of Profit_1 for loss 0.0477903522728147\n",
      "The probability of Profit_2 for loss 0.040059156863817086\n"
     ]
    }
   ],
   "source": [
    "print(\"The probability of Profit_1 for loss\",stats.norm.cdf(0,5,3))\n",
    "print(\"The probability of Profit_2 for loss\",stats.norm.cdf(0,7,4))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "63b3be40",
   "metadata": {},
   "source": [
    "# set-03"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "aed0b0a0",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Q-no 07\n",
    "a=stats.norm.interval(0.95)\n",
    "b=stats.t.interval(0.95,5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "11f8748b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-1.959963984540054, 1.959963984540054)"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "92404264",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-2.5705818366147395, 2.5705818366147395)"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "470f2b22",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.959963984540054"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stats.norm.ppf(0.975)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "9b9ca457",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2.3263478740408408"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stats.norm.ppf(0.99)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ca7e2a60",
   "metadata": {},
   "source": [
    "# set - 04"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "2fe38621",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "the Z-score range is : -0.125 to 0.125\n"
     ]
    }
   ],
   "source": [
    "# qns no 03\n",
    "# Z-score for the values range 45 to 55\n",
    "Z1=(45-50)/40\n",
    "Z2=(55-50)/40\n",
    "print (\"the Z-score range is :\",Z1,\"to\",Z2 )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "e5057c71",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.2124433347629998"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#probability that \n",
    "2*stats.norm.cdf(0.125,50,40)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "3fc86a94",
   "metadata": {},
   "outputs": [],
   "source": [
    "#the probability that in any given week, there will be an investigation is \n",
    "## 21.1%"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "482cb28e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "the Z-score for 5% pprobability is -1.96\n"
     ]
    }
   ],
   "source": [
    "#qns no 04\n",
    "print(\"the Z-score for 5% pprobability is\",round(stats.norm.ppf(.025),3))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0a4ac253",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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