CS-0206: Introduction to Statistics
This class is an introduction to descriptive and inferential statistics that are useful for analyzing data from a variety of fields. Topics covered include summary statistics, graphical methods, and resampling and parametric inference methods for calculating confidence intervals and conducting hypothesis tests. Students will learn how to use the R programming language to explore statistical concepts and to analyze real data. Assignments will consist of weekly problem sets and a final class project where students will gain experience analyzing a dataset in more depth. By the end of the class students will be able to understand the concepts that underlie statistical analyses and will be able to apply statistical methods to gain insight into data that they collect.
Resources
Class resources: syllabus, class slack channel
R resources: R tutorial, R Markdown cheat sheet, Learning R videos: Intro, common functions, vectors, descriptive statistics, Visualizing Univariate Data, scatter plots
Shiny Apps: Gettysburg sampling distribution app, Sampling and bootstrap distribution app, Normal area app, Normal range app, Quantile area app (these ran on a Hampshire College server that is no longer online)
R Markdown worksheets: Worksheet 1, Worksheet 2, Worksheet 3, Worksheet 4, Worksheet 5, Worksheet 6, Worksheet 7, Worksheet 8, Worksheet 9, Worksheet 10, Worksheet 11, Worksheet 12
PDFs of the worksheets: Worksheet 1, Worksheet 2, Worksheet 3, Worksheet 4, Worksheet 5, Worksheet 6, Worksheet 7, Worksheet 8, Worksheet 9, Worksheet 10, Worksheet 11, Worksheet 12
Schedule
Class 1: Class overview
Class 2: Introduction to R
Class 3: Sampling and categorical data analysis
Worksheet 1
Class 4: Quantitative variables and measures of central tendency
Class 5: Quantitative variables and measures of spread
Standard deviation in class worksheet
Worksheet 2
Class 6: Percentiles, boxplots, and z-scores
Worksheet 3
Class 7: Relationships between quantitative variables
Boxplot & Histogram app
Correlation game app
Class 8: Review
Worksheet 4
Class 9: Sampling, bias and sampling distributions
Sampling handout
Worksheet 5
Class 10: Sampling distributions and interval estimates
Gettysburg sampling distribution app
Class 11: Confidence intervals
Worksheet 6
Class 12: Standard errors and the bootstrap
Sampling and bootstrap distribution app
Worksheet 7
Class 13: Hypothesis tests and p-values
Class 14: Hypothesis tests for a single proportion
Worksheet 8
Class 15: Hypothesis tests comparing two means
Worksheet 9
Class 16: Hypothesis tests comparing more than two means and paradigms of hypothesis testing
Class 17: Hypothesis tests for correlation
Worksheet 10
Class 18: Probability distributions
Normal area app, Normal range app, Quantile area app
Class 19: Inference using normal distributions
Class 20: Parametric inference on proportions
Worksheet 11
Class 21: Parametric inference on a single mean
Final project template
Final project example
Class 22: Parametric inference on two means
Worksheet 12
Class 23: Final project presentations (slides unavailable)
Class 24: Final project presentations
Class 25: Conclusions (slides unavailable)