everything.study
AP/ADMS 4370

Data Analysis Systems

3.0 credits

Fall 2026

Topics

  • R and RStudio for data analysis
  • Exploratory statistics and visualization
  • Probability, sampling and the central limit theorem
  • Confidence intervals, hypothesis tests and ANOVA
  • Simple and multiple regression
  • Reproducible reporting in R Markdown or Quarto
  • Contingency tables and chi-square tests
  • Logistic regression, classification and ROC curves
  • Rank-based and other nonparametric methods

Readings

  • Optional: James, Witten, Hastie and Tibshirani, An Introduction to Statistical Learning: With Applications in R, 2nd ed. (Springer, 2021).
  • Optional: Diez, Barr and Çetinkaya-Rundel, OpenIntro Statistics.
  • Optional: David Dalpiaz, Applied Statistics with R.
  • Optional: Wickham and Grolemund, R for Data Science (O'Reilly, 2017).
  • Optional: UCLA Statistical Consulting Group, R Statistical Computing Learning Modules.
  • Optional: Bowerman and O'Connell, Linear Statistical Models: An Applied Approach, 2nd ed. (Duxbury, 2000).
  • Optional: Hosmer and Lemeshow, Applied Logistic Regression, 2nd ed. (Wiley).
  • Optional: E. M. Nussbaum, Categorical and Nonparametric Data Analysis: Choosing the Best Statistical Technique, 2nd ed. (2024).
  • Optional: Gerald Keller, Statistics for Management and Economics.
Sources