## reading data 
## note the use of read.csv () function rather than read.table()
nyc = read.csv('http://www.stat.tamu.edu/~sheather/book/docs/datasets/nyc.csv',header=TRUE)

## reformatting
nam = nyc[,2]
nyc= nyc[,3:6] # getting rid of columns useless here
rownames(nyc) = nam # we need the names but it is not a variable

## EDA
pairs(nyc)


## Three different ways to fit the same full model
res = lm(formula = Price ~ 1 + Food + Service + Decor,data=nyc)

res = lm(formula = Price ~ 1 + Food + Service + Decor,data=nyc)

res =  lm(formula = Price ~ .,data=nyc)

res

summary(res)

## Comparing significance of the Service parameter
## in a model that does not contain decor
summary(lm(formula = Price ~ 1 + Food + Service + Decor,data=nyc))