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Lecture Notes

by Elizabeth Purdom and Adityanand Guntuboyina

# Title Chapter (pdf) Code (html) Code(Rmd)
01 Review of probability pdf html Rmd
02 Comparing Groups and Hypothesis Testing pdf html Rmd
03 Fitting curves to data pdf html Rmd
04 Visualizing Multivariate Data pdf html Rmd
05 Multiple Regression pdf html Rmd
06 Logistic Regression pdf html Rmd
07 Regression and Classification Trees pdf html Rmd

Labs

by Boying Gong

# Title Jupyter Link
01 Intro to R link
02 Intro to RStudio link
03 Density curves, violin plots link
04 Permutation tests, t-tests, Bonferonni correction link
05 Bootstrap and parametric Confidence Intervals, Linear regression link
06 Linear models, plotting, polynomial models link
07 Loess and Pairs plots link
08 Heatmaps, PCA, brief intro to ggplot link
09 More PCA link
10 Multiple linear regression models link
11 Prediction with linear regression link
12 Regression diagnostics and logistic regression link
13 Regression and classification trees link