The contents/materials for Stat 425 may vary from semester to semester, subject to change/revision at the instructor’s discretion. The contents below are from Fall 2017.

F = Textbook by J. Faraway; S = Textbook by S.J. Sheather

• Introduction
  [Note_Intro] [Prerequisite]
  Reading: chap 1 (F); chap 1 (S)

• Simple linear regression
  [Note_SLR] [R_SLR1] [R_SLR2]
  Reading: chap 2 (S)

• Multiple linear regression
  [Note_MLR] [R_MLR1] [R_MLR2] [MLR_appendix] [Note_Projection]
  Reading: chap 2,3 (F); chap 5 (S); chap1~5 (JM)

• Analysis of Covariance
  [Note_AnCova] [R_AnoCov]
  Reading: chap 15 (F); chap 5.3 (S)

• Diagnostic
  [Note_Diag] [R_Diag1] [R_Diag2] [Diag_appendix]
  Reading: chap 6 (F); chap 3,6 (S)

• Generalized least squares
  Testing for lack of fit
  [Note_GLS] [R_GLS]
  Reading: chap 8.1-8.3 (F); chap 4,9 (S);
  Collinearity
  [Note_Collinear] [R_Collinear]
  Reading: chap 7.3 (F); chap 6.4 (S)

• Polynomial regression
  [Note_poly] [R_poly] [birthrates.txt]
  Reading: chap 9 (F); chap 3.3, 6.2 (S)
  Additional Reading: Chap 7 from ISLR
  Nonparametric regression and spline models
  [note_nonpa] [R_nonpa] [R_spline]
  Reading: “STL: A Seasonal-Trend Decomposition Procedure Based on Loess”

• One-way and two-way ANOVA
  [Note_ANOVA1] [Note_ANOVA2] [Note_ANOVA3] [R_ANOVA] [R_ANOVA2]
  Reading: chap 14-16 (F); chap 2.6 (S); chap 6~8 (JM)
  Blocking designs and higher order ANOVA
  [Note_blocking] [R_blocking]
  Reading: Chap 17 (F); [Experimental Design] from NIST; [Blocking Lecture] From PSU

• Variable selection
  [Note_varsel][R_varsel] [R_varsel_add]
  [Download dig14.Rdata]
  Reading: chap 10, 11 (F); chap 7 (S).
  Additional Reading: Chap 6 from ISLR

• Tree models
  [Note_tree] [R_tree] [RandomForests]

• Logistic regression
  [Note_logisticc] [R_logistic]
  Reading: chap 8 (S)