An introduction to statistics in R

statistics
intro
learning R
Author

Dr. Joscelin Rocha-Hidalgo

Published

April 22, 2025

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By Mark Peterson

Excerpt from site: A series of tutorials by Mark Peterson for working in R

  1. Link to site here: http://petersonbiology.com/math230Notes/dataInR.html

Chapter Navigation

  1. Basics of Data in R

  2. Plotting and evaluating one categorical variable

  3. Plotting and evaluating two categorical variables

  4. Analyzing shape and center of one quantitative variable

  5. Analyzing the spread of one quantitative variable

  6. Relationships between quantitative and categorical data

  7. Relationships between two quantitative variables

  8. Final Thoughts on linear regression

  9. A bit off topic - functions, grep, and colors

  10. Sampling and Loops

  11. Confidence Intervals

  12. Bootstrapping

  13. More on Bootstrapping

  14. Hypothesis testing and p-values

  15. Differences in proportions and statistical thresholds

  16. Hypothesis testing for means

  17. Final thoughts on hypothesis testing

  18. Approximating with a distribution model

  19. Using the normal model in practice

  20. Approximating for a single proportion

  21. Null distribution for a single proportion and limitations

  22. Approximating for a single mean

  23. CI and hypothesis tests for a single mean

  24. Approximating a difference in proportions

  25. Hypothesis test for a difference in proportions

  26. Difference in means

  27. Difference in means - Hypothesis testing and paired differences

  28. Shortcuts

  29. Testing categorical variables with Chi-sqare

  30. Testing proportions in groups

  31. Comparing the means of many groups

  32. Linear Regression

  33. Multiple Regression

  34. Basic Probability

  35. Random variables

  36. Conditional Probability

  37. Bayesian Analysis

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