nflcomb <- read.csv("http://www.stat.ufl.edu/~winner/sta4210/mydata/nfl_combine.csv",
       header=TRUE)
attach(nflcomb); names(nflcomb)

#### Obtain the Training and Validation Samples, generated in EXCEL
#### Selects all rows where Sample is 1 or 2, and all columns  
#### nflcomb[rows,cols]

nfl.train <- nflcomb[Sample==1,]
nfl.valid <- nflcomb[Sample==2,]

#### Fit the Regression model for the Training and Validation Samples

train.mod <- lm(Weight ~ Height + ArmLng + HandLng, data=nfl.train)
valid.mod <- lm(Weight ~ Height + ArmLng + HandLng, data=nfl.valid)
summary(train.mod)
summary(valid.mod)

#### Compute the fitted values for Validation sample from Model fitted
####   to Training Sample (Note that X1, X2, X3 are in Columns 4, 5, 6)
####   and Y is in Column 7
####  Compute MSEP

yhat.val <- predict(train.mod,nfl.valid[,4:6])
e.val <- nfl.valid[,7] - yhat.val
(MSEP <- sum(e.val^2)/nrow(nfl.valid))