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\title{Foodstamp - Residuals of Logistic Regression}

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Load and attach the data foodstamp.
<<results='hide',eval=FALSE>>=
library(catdata)
data(foodstamp)
attach(foodstamp)
@
With binary resonse one can fit a logit model.
<<eval=FALSE>>=
food1 <- glm(y ~ TEN + SUP + INC, family=binomial, data=foodstamp)
summary(food1)
@
Have a look at the distribution of the residuals. Therefore a Normal Q-Q Plot is generated.
<<eval=FALSE>>=
plot(food1,2)
@

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