Lab Projects

Introduction

Lab projects are assigned in the syllabus. As you will see, there is roughly one per week. On the date in the syllabus, we'll spend the 2nd half of class working on the project. Try to have the bulk of it done ahead of time, so that you can focus on the hard parts during lab. After the lab meeting, you'll have another week to tidy it up before the report on that project is due. Meanwhile, I'll have assigned another project. Thus, there will usually be two projects in play: a new one that you're trying to figure out, and an old one for which you're preparing a lab report.

What to turn in

For each project, please email a single plain-text file consisting of R code and ending with the suffix ".r". Make sure you can execute this file from the R interpreter with the command source("myfile.r", echo=T), where myfile.r is the name of your file. If your name is "Alan Rogers", then your report for lab 3 should be named "AlanRogers3.r".

Within the file, include all the R code needed for your lab report, but don't include anything I don't need to see. If it took you several tries to get something right, just show me the last version.

Most projects consist of a numbered series of exercises. Please use this framework to organize your lab report. Your report should contain a numbered section for each numbered exercise in the lab project. Use comments to number the sections.

Your report should also include text, in the form of comments. Use comments to tell me what you are doing and to discuss the implications of each graph you present. These discussions are just as important as the graphs themselves.

Projects

  1. Introduction to R

  2. Quantile-quantile plots

  3. Tukey mean-difference plots, box plots, and one-way fits

  4. The history of brain size

  5. Hormones

  6. Permutation tests

  7. The bootstrap

  8. Likelihood