Liz Milano, of the Juenger lab, will be giving us an overview of multivariate datasets.

The multivariate stats class will cover:

-Basic summary tools for genetic and non-genetic multivariate datasets

-Data reduction

-Variance/covariance matrices

-Theory, implementation, and visualization of Principal Components Analysis

-and if we have time, other flavors of coordinate analysis

The lecture will be part chalk talk, part slides and part tutorial. Required packages are ade4 and adegenet and optional packages are psych and car. We will also be using the following datasets:

data(iris)

data(microbov)

wine <- read.table("http://archive.ics.uci.edu/ml/machine-learning-databases/wine/wine.data", sep=",") #noms

Lecture:

multivariate_lecture.pptx

R code:

multivariate_stats.R

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