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USING R:

x variable = income, y variable = sales; data set = Carseats how would you code this?

In this part of the problem, we will find a polynomial function of Income that best fits the Carseats data. For each polynomial function between p 0,1,2,..10: i. Fit a linear regression to predict Sales as a function of Income, Income2. IncomeP (you should include an intercept as wel. Note that p 0 model is an intercept-only model.

math   Statistics-And-Probability   
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Answer #1

The R code for the required question is

attach(carseats)
model <- lm(y ~ poly(x,10))

summary(model)

here poly function 10 , creates predictor variables as x1 , x^2,x^3,x^4 ,.... x^10

summary function would give all the results related to the fitted regression equation

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