Stat 471/571 - Spring 2023 - R programs

Week of 10 April:

• asparagus.r and Explanation document
  Data file is asparagus.csv
• indepTest.csv Data set used to demonstrate differences between functions fitting an independence model.

Week of 27 March:

• Split plot code and Explanation document
  The description of the PA study is here
  Data files are pa2.xlsx and PA.csv.

Week of 20 March:

• delury.r Code to fit ANCOVA models, with "after the ANOVA" computations
• Explanation document for delury.r
• delury.xlsx Data file for delury.r

Week of 1 March:

• Background and summary of conclusions for a 2x2 factorial.
• adoptIQ.r 2 way factorial: R code to analyse the nature/nurture data set
• adoptIQ.xlsx Data set for the nature / nurture problem.
• Notes / explanation on the 2 way factorial R code
• Analysis of unbalanced factorial data in R: what works and what doesn't
• brome.r Analysis of Latin Squares and repeated Latin Squares
  Data files are brome.csv (Latin Square) and brome2.csv (repeated Latin Square)

Week of Feb 13:

• Analysis of block designs and Explanation
  Data file is mead53b.csv
• Transforming the response variable and Explanation.
  Includes using emmeans functions to do the back transformation.
  Data file is hamburger.xlsx. This example is a two-sample comparison.

Week of Feb 6:

• Variance components, explanation, and data file, salinity.csv
• Summarizing data and piping (Stat 587 lab information), Explanation, and data file patty.txt

Week of Jan 24:

• PowerR.r Code to compute the three examples in the week 2 notes. Followed by illustration of power.t.test().
• PowerR.pdf Explanation of code in powerR.r.
• dietall2.r Code for fitting an ANOVA model and computing contrasts. Requires dietall.csv
• Explanation of fitting an ANOVA model and computing contrasts

Week of Jan 17:

• Calculating quantiles of T distributions Explanations are comments in the code.

R review:

• If you need a review of R for 301/587 material, look at my R lab material for Stat 587
• If you are just starting to learn R, here are two tutorials
  • Introduction to R Getting started with R. My choice of a basic tutorial.
  • Tutorial on R, From U GA lots of information - more than needed for this class