From a68a81a311aa8bba4a10a362c096c17bf3965039 Mon Sep 17 00:00:00 2001
From: Alexandre Garanhao <alexgaranhao@sapo.pt>
Date: Tue, 23 May 2023 11:06:12 +0100
Subject: [PATCH] lab done

---
 your_code/main.ipynb | 97 ++++++++++++++++++++++++++++++++++++++------
 1 file changed, 85 insertions(+), 12 deletions(-)

diff --git a/your_code/main.ipynb b/your_code/main.ipynb
index 7810ccf..95b0cd2 100644
--- a/your_code/main.ipynb
+++ b/your_code/main.ipynb
@@ -1,6 +1,7 @@
 {
  "cells": [
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -14,14 +15,42 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 2,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Power_divergenceResult(statistic=6.491310681109786, pvalue=0.483688906853731)"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "# your answer here"
+    "# your answer here\n",
+    "\n",
+    "from scipy.stats import poisson\n",
+    "from scipy.stats import chisquare\n",
+    "\n",
+    "observed = [35, 99, 104, 110, 62, 25, 10, 3]\n",
+    "\n",
+    "expected = [poisson.pmf(0, 2.435)*448, \n",
+    "            poisson.pmf(1, 2.435)*448, \n",
+    "            poisson.pmf(2, 2.435)*448, \n",
+    "            poisson.pmf(3, 2.435)*448, \n",
+    "            poisson.pmf(4, 2.435)*448, \n",
+    "            poisson.pmf(5, 2.435)*448, \n",
+    "            poisson.pmf(6, 2.435)*448, \n",
+    "            (1-poisson.cdf(6, 2.435))*448]\n",
+    "\n",
+    "chisquare(f_obs= observed, f_exp= expected)"
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -41,14 +70,34 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 3,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Power_divergenceResult(statistic=6.248550837473296, pvalue=0.012429495465327692)"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "# your code here"
+    "# your code here\n",
+    "observed = [32, 15, 13]\n",
+    "estimated_mean = (32*0+15*1+9*3+4*4)/60\n",
+    "\n",
+    "expected = [poisson.pmf(0, estimated_mean)*60,\n",
+    "            poisson.pmf(1, estimated_mean)*60,\n",
+    "            (1-poisson.cdf(1, estimated_mean))*60]\n",
+    "\n",
+    "chisquare(f_obs= observed, f_exp= expected, ddof= 1)"
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -60,14 +109,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# your answer here"
+    "# your answer here\n",
+    "\n",
+    "from scipy.stats import binom\n",
+    "observed = [138, 53, 9]\n",
+    "expected = [binom.pmf(0, 10, 0.05)*200, \n",
+    "            binom.pmf(1, 10, 0.05)*200, \n",
+    "            (1-binom.cdf(1, 10, 0.05))*200]"
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -79,11 +135,28 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 5,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Chi2ContingencyResult(statistic=10.712198008709638, pvalue=0.004719280137040844, dof=2, expected_freq=array([[24.08421053, 19.91578947],\n",
+       "       [19.70526316, 16.29473684],\n",
+       "       [ 8.21052632,  6.78947368]]))"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "#your answer here"
+    "#your answer here\n",
+    "import numpy as np\n",
+    "from scipy.stats import chi2_contingency\n",
+    "table = np.array([[32, 12], [14, 22], [6, 9]])\n",
+    "chi2_contingency(table)"
    ]
   }
  ],
@@ -103,7 +176,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.3"
+   "version": "3.11.2"
   }
  },
  "nbformat": 4,