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authorJulian T <julian@jtle.dk>2021-03-12 11:56:20 +0100
committerJulian T <julian@jtle.dk>2021-03-12 11:56:20 +0100
commit8430a7f363589260c809f180bfa2c0a7097d5e6b (patch)
tree8570ea72000616e7f59d66285615cf9013905a94 /sem6/prob/stat3
parent1455ccc4eb1047aba2a50b8c2c3a5bd3887d0226 (diff)
Added assignments for prob
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+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 10,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import numpy as np\n",
+ "from scipy.stats import norm\n",
+ "from IPython.display import display, Math, Markdown\n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Opgaver\n",
+ "\n",
+ "Har lavet problem 1 på papir, men vil lave resten i python da det nok er lidt lettere."
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Problem 2\n",
+ "\n",
+ "Går ud fra at PCB er i ppm, og kalder den $\\theta$.\n",
+ "\n",
+ "$$\n",
+ "X_i = \\theta + W_i\n",
+ "$$\n",
+ "hvor $W_i \\sim \\mathcal{N}(\\mu, \\sigma^2)$, $\\sigma = 0.08$.\n",
+ "Her går jeg ud fra at $\\mu = 0$.\n",
+ "\n",
+ "Derfor er: \n",
+ "$$\n",
+ "E[X] = \\theta\n",
+ "$$\n",
+ "og\n",
+ "$$\n",
+ "Var[X] = (0.08)^2\n",
+ "$$\n",
+ "\n",
+ "Kan sige at confidence level er:\n",
+ "$$\n",
+ "[\\bar{X} - z_{\\frac \\alpha 2} \\cdot \\frac \\sigma {\\sqrt{n}}, \\bar{X} + z_{\\frac \\alpha 2} \\cdot \\frac \\sigma {\\sqrt{n}}]\n",
+ "$$\n",
+ "with probability $1-\\alpha$.\n",
+ "Her er \n",
+ "$$\n",
+ "z_p = \\Phi^{-1}(1 - p)$$"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 11,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "samples = [11.2, 12.4, 10.8, 11.6, 12.5, 10.1, \n",
+ " 11.0, 12.2, 12.4, 10.6]\n",
+ "n = len(samples)\n",
+ "\n",
+ "X_bar = np.mean(samples)\n",
+ "sigma = 0.08"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 15,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/latex": [
+ "$\\displaystyle P(11.430416397415636 \\leq \\theta \\leq 11.529583602584365) = 0.95$"
+ ],
+ "text/plain": [
+ "<IPython.core.display.Math object>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# Del A\n",
+ "alpha = 0.05\n",
+ "Z = norm.ppf(1 - alpha/2)\n",
+ "\n",
+ "dist = Z * sigma / np.sqrt(n)\n",
+ "lower = X_bar - dist\n",
+ "upper = X_bar + dist\n",
+ "\n",
+ "display(Math(f\"P({lower} \\\\leq \\\\theta \\\\leq {upper}) = {1 - alpha}\"))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 18,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/latex": [
+ "$\\displaystyle [-\\infty, 11.529583602584365]$"
+ ],
+ "text/plain": [
+ "<IPython.core.display.Math object>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "\n",
+ "# Okay så lower confidence level er åbenbart at man går fra -infty til upper limit\n",
+ "\n",
+ "display(Math(f\"[-\\\\infty, {upper}]\"))\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 21,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/latex": [
+ "$\\displaystyle [11.430416397415636, \\infty]$"
+ ],
+ "text/plain": [
+ "<IPython.core.display.Math object>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# Del C\n",
+ "# Og igen for uppwer\n",
+ "\n",
+ "display(Math(f\"[{lower}, \\\\infty]\"))"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3",
+ "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": "3.9.2"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}