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add week 12 R materials
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mgyliu committed Apr 8, 2024
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376 changes: 376 additions & 0 deletions materials/R/tutorial_activity_inference2/tutorial_activity_inference2.ipynb
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{
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"source": [
"# DSCI 100: Introduction to Data Science\n",
"\n",
"## Tutorial 12 - Bootstrapping and Confidence Intervals"
]
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"source": [
"First, load the necessary libraries."
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"### Run this cell before continuing\n",
"library(tidyverse)\n",
"library(repr)\n",
"library(digest)\n",
"library(infer)\n",
"library(gridExtra)"
]
},
{
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"source": [
"Let's revisit our students from last week."
]
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"source": [
"# run this cell to simulate a finite population\n",
"set.seed(12341)\n",
"students_pop <- tibble(grade = (rnorm(mean = 70, sd = 8, n = 10000)))\n",
"head(students_pop)"
]
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"source": [
"To figure out the class average, you ask the 50 classmates in your groupchat. Draw a single sample of size 50 from the population. Drop the `replicate` column by using `ungroup()` followed by `select()`."
]
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"set.seed(12341)\n",
"\n",
"# your code here\n",
"fail() # No Answer - remove if you provide an answer\n",
"\n",
"head(sample)"
]
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"You don't know anyone else in the class, so the best way to estimate the class average is by bootstrapping. Take 100 bootstrap samples from the sample you just drew. "
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"set.seed(12341)\n",
"\n",
"# your code here\n",
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"\n",
"head(bootstrap)"
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"Calculate the mean for each set of bootstrap samples and visualize the distribution using a histogram with `binwidth = 0.5`. "
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"# your code here\n",
"fail() # No Answer - remove if you provide an answer\n",
"\n",
"bootstrap_dist"
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"Using this bootstrap distribution, calculate 95% and 80% confidence intervals. Which interval has a wider range?"
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"\n",
"bootstrap_95\n",
"bootstrap_80"
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"Finally, calculate the mean of the original population. Which of our confidence intervals encapsulate the true population mean?"
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"mean(students_pop$grade)"
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1 change: 1 addition & 0 deletions materials/R/worksheet_inference2/cleanup.R
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# clean up data files that students output
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