A company wants to predict sales as a function of various other quantities including advertising spend, and whether it is summer (coded as 1 for summer, 0 for the rest of the year). These are named sales, ad spend, summer in the dataset in R, and the dataset is called sales data.

The following R commands are run: model1 =1m (sales ad_spend+summer, data=sales_data) summary (model1) Part of the output is: Coefficients: (a) What are the interpretations of the coefficients for ad_spend and summer? (b) From this model, do sales appear to be significantly related to advertising spend? (c) If the following R command is run: predict (model1, newdata=data.frame(ad_spend =200, summer=1)) what will the numerical output be? What is the interpretation of this quantity? (d) The following R commands are run to produce the plot below: plot (x= model1\$fitted.values, y= model1\$residuals) abline (h=0)