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Lab 2: Basics of Using R

**How to start**

**How to load data**

Local data/remote files: e.g, mydata <- read.csv("http://www.ats.ucla.edu/stat/data/binary.csv") (download the data)

Data of different formats: read.csv(), read.table()
**Example 1: a Gaussian distribution**

Get the code from here, or

Call it remotely: source("http://mendel.informatics.indiana.edu/~yye/lab/teaching/spring2013-I529/gaussian-demo.R")

try: y <- pnorm(15, mean=mean(x.norm), sd=sd(x.norm))
**Example 2: not-so-simple linear fitting**

Get the code from here, or

Call it remotely: source("http://mendel.informatics.indiana.edu/~yye/lab/teaching/spring2013-I529/lm-demo.R")
**Example 3: logistic linear regression (generalized linear models)**

Get the code from here, or

Call it remotely: source("http://mendel.informatics.indiana.edu/~yye/lab/teaching/spring2013-I529/logit-demo.R")

see this tutorial

see an introduction on logistic regression

see a paper on Logistic regression for disease classification