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Useful Links/Downloads

• There are two textbooks for this course
  • OpenIntro: You can download this textbook for FREE. In addition to the textbook, their website has additional lecture slides, video lectures, and labs for practicing R. This book will generally be used for everything but probability.
  • From Algorithms to Z-Scores: Probabilistic and Statistical Modeling in Computer Science: Again, this book can be downloaded entirely for free. This book will be useful for the more mathematical introduction to probability that is beyond the scope of OpenIntro.
• A fast, practical way to learn R is through the swirl package. Follow the instructions from that link to go through a few tutorials.
• Rstudio has made some very useful cheat sheets that you can reference while you are programming in R. I’ve placed some of the more useful ones for this class here:
  • Base R
  • Data Wrangling
  • ggplot2
  • Data Import
  • Rstudio IDE
• In addition, I wrote up a brief cheat sheet for R Base graphics.

Lectures

Note: Each lecture is a topic, not a day of class.

1. Course Outline
2. Data Basics
3. Histograms
4. Center/Spread
5. Quantiles
6. Categorical Variables
7. Case Study: Trump’s Tweets
8. Densities
9. Normal Density Calculations
10. Sampling Distributions
11. Probability and Sets
12. Proofs from Axioms of Probability
13. Conditional Probability and Independence
14. Bayes Rule
15. Discrete Random Variables
16. Binomial Distribution
17. Continuous Random Variables
18. Multiple Random Variables
19. Moment Generating Functions
20. Central Limit Theorem Motivation
21. Central Limit Theorem Proof
22. Linear Approximation to Exponential
23. Exponential Approximation
24. Interval Estimates for Means
25. Some Confidence Interval Examples
26. Hypothesis Testing for Means
27. Inference for Means in Small Samples
28. Differences of Means
29. Inference for Proportions
30. Simple Linear Regression
31. Multiple Linear Regression
32. Review

Stat Comics That Made Me Laugh

• SMBC:
  • Effect size
  • Allegorical Evidence
  • Hypothesis Testing
  • Bayesian Drinking
  • Small Sample Size
  • Type I Error Control
• XKCD:
  • Outliers
  • Correlation and Causation
  • Extrapolation
  • Bad Plots
  • Publication Bias
  • Usually Use Proportions, not Counts
  • p-values
  • Violin Plots
  • Curve Fitting
  • Selection Bias

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