Stat 401A - Lab Activities - R version

Lab activities - R version

Hints for downloading and accessing files

Lab 1: 10 Jan

Lab 1 activities Read this first
Introduction to R Getting started with R.
creativity1.pdf Explanation of code in creativity1.r.
creativity1.r R code file

Lab 2: 17 Jan

creativity2.pdf Explanation of code in creativity2.r.
creativity2.r R code file
Lab 2 self assessment

Lab 3: 24 Jan

creativity3.pdf Explanation of code in creativity3.r.
creativity3.r R code file
Lab 3 self assessment

Lab 4: 31 Jan

case0202.txt, Data for Schizophrenia case study
hamburger.csv, Data for hamburger example (csv format)
hamburger.xlsx, Data for hamburger example (xlsx format)
pairedt.pdf Explanation of code in pairedt.r.
pairedt.r R code file
hamburger.pdf Explanation of code in hamburger.r.
hamburger.r R code file
Lab 4 self assessment
fishprice.txt fish price data for self assessment

Lab 5: 7 Feb

resids.r Code to plot residuals and draw QQ plots
resids.pdf Explanation of code in resids.r
alanine.csv Alanine data set for self assessment
Lab 5 self assessment

Lab 6: 14 Feb

calcmeans.r Calculating and saving means and residuals
patty.txt, data for calcmeans.r
Explanation of code in calcmeans.r
arabidop.csv, data for lab 6 self assessment
Lab 6 self assessment

Lab 7: 28 Feb

dietall.r Summarizing data using pipes, Fitting ANOVA models, "after the ANOVA"
case0501.csv, data for dietall.r, Case study 1 in Chapter 5: mouse diet and longevity study
Explanation of code in dietall.r
cavity.txt Data for self assessment exercise
Lab 7 Self assessment

Lab 8: 7 March

fdr.r False discovery rate, starting from p-values for each test.
Explanation of code in fdr.r
manyP.csv File with p-values, one row per test.
meat1.r Fitting a linear regresion
Explanation of code in meat1.r
meat.txt Meat pH over time data set.
Self assessment on FDR and estimating a linear regression
pvalues.csv data file for self assessment
GFCLOCKS.txt data file for self assessment

Lab 9: 21 March

meat.r More linear regression: confidence and prediction intervals, ANOVA lack of fit test
Explanation of code in meat.r
Self assessment on more linear regression
GFCLOCKS.txt data file for self assessment

Lab 10: 28 March

brain.r Scatterplot matrices, correlations, Multiple regression
Explanation of code in brain.r
corn.r Polynomial regression
Explanation of code in corn.r
Self assessment on multiple linear regression
tamsales1.txt data file for self assessment

Lab 11: 10 Apr

light.r Creating indicator variables
Explanation of code in light.r
Light.txt Data file for light and flowering time study, for light.r
sat.r Model selection and multiple regression diagnostics
Explanation of code in sat.r : updated 24 April.
sat.xslx Data file for SAT problem
Self assessment on model selection
modelsel.csv data file for self assessment

Lab 12: 18 Apr

collard.r 2 way factorial ANOVA
Explanation of code in collard.r
collard.txt Data for collard study
vitc.r Contingency table and proportions
Explanation of code in vitc.r
vitc.txt Data for Vitamin C study
viotclong.csv Data for Vitamin C study, long format

Lab 13: 25 Apr

donner.r Logistic regression
Explanation of code in donner.r
donner.csv Donner part data
matings.r Analysis of count data
Explanation of code in matings.r
matings.csv Elephant matings data set

General information: Installing R:

R is a freedownload: go to ISU mirror site for CRAN, the Comprehensive R Archive Network. Choose the edition appropriate for your operating system, download the installer and install R. You will need administrative rights to install R.
Many people prefer to use R through R Studio, a development environment that provides an interface to R. If you want to use R Studio, download and install R first (see above), then download and install R Studio from the download site You want R Studio Desktop / Open Source license. That is currently free.

General Information: Useful guides to R:

There are many, many "Intro to R" documents around the web. One I find especially useful is The Montana State Ecology group's version.
The R project has an Intro to R document. This is the official version but I find it has way more than you need to know. Go to CRAN, choose Manuals in the left frame, then Introduction to R / R release. A copy that is specific to your operating system and R version is included with the installation package. Search for Rintro.pdf in the Program Files folder or its Mac or Linux alternative.