AS FM
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"cells": [
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"%matplotlib widget\n",
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"from collections.abc import Iterable\n",
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"\n",
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"import matplotlib.pyplot as plt\n",
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"import numpy as np\n",
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"from scipy.stats import chi2\n",
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"import math\n",
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"from fractions import Fraction as F"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# AS\n",
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"This contains automations for A-level (AS) Maths stats ordered in the same way as they are on [integral maths](https://my.integralmaths.org/)."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Collecting and Interpreting Data\n",
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"### Sampling\n",
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"- Simple random sampling\n",
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" - Random procedure\n",
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" - e.g. drawing tickets, random number generator\n",
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" - In a finite sample space, all candidates have an equal chance of being selected\n",
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" - Sampling is done without replacement\n",
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" - Selections are independent\n",
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"- Cluster sampling\n",
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" - Only some subgroups of a sample space are selected\n",
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" - Only appropriate when subgroups are reasonably representative of the entire sample space\n",
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"- Opportunity sampling\n",
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" - Selection by opportunity\n",
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" - e.g. interviewing passers by on a street\n",
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"- Stratified sampling\n",
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" - Used when sample space can be divided into subgroups (strata)\n",
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" - ... to ensure all strata are sampled\n",
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" - Weighting needs to be used if numbers of samples from each strata are not proportional to the size of the strata\n",
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"- Quota sampling\n",
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" - Same as stratified sampling with a quota for each strata\n",
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"- Self-selected sample\n",
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" - Individuals chose to be sampled\n",
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" - e.g. online poll\n",
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"- Systematic sampling\n",
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" - Systematic procedure\n",
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" - e.g. every 10th person on alphabetically sorted list"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"name": "python",
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"version": "3.9.2 (default, Feb 28 2021, 17:03:44) \n[GCC 10.2.1 20210110]"
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},
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"orig_nbformat": 4,
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"vscode": {
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"interpreter": {
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"hash": "31f2aee4e71d21fbe5cf8b01ff0e069b9275f58929596ceb00d14d90e3e16cd6"
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}
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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