The following books have served as references while writing Foundations of Applied Statistics:

  • All of Statistics, by Larry Wasserman
  • All of Nonparametric Statistics, by Larry Wasserman
  • The Elements of Data Analytic Style, by Jeff Leek
  • The Elements of Statistical Learning, by Hastie, Tibshirani, and Friedman
  • Nonparametric Regression and Generalized Linear Models: A roughness penalty approach, by Green and Silverman
  • Pattern Recognition and Machine Learning, by Christopher Bishop
  • R for Data Science, by Wickham and Grolemund
  • R Programming for Data Science, by Roger Peng
  • Statistical Inference, by Casella and Berger