Question

Questions should be answered using the Answer Sheet Template with your name at the top. All relevant R codes, numeric answers and conclusions should be provided. No screenshots are required. Note, only R should be used to answer the questions, as needed. Answers should be written in the appropriate row of the Answer Sheet (ie., corresponding to the question number). The report should be individually uploaded in BB by the due date. Question A: 3*26 points The following data gives the monthly sales (in thousands of dollars) for different advertising expenditures (also in thousands of dollars) and sales commission percentages. Sales Advertising Commission 245 138 352 322 228 275 560 366 16.5 18.0 22.3 17.4 19.0 20.0 32.0 18.6 10.5 2.0 4.0 3.5 4.5 1.8 9.0 8.5 1. What amount of sales would this model predict for advertising expenditures of 25,000 and sales commission of 8%? [Write in R Code & Answer of Question 1] At the 5% level of significance, is either advertising expenditure or sales commission percentage or both significant? Why? [Write in R Code, Answer & Conclusion of Question 2] 2.

The following data gives the monthly sales (in thousands of dollars) for different advertising expenditures (also in thousands of dollars) and sales commission percentages. Help me solve this R code, thanks

Answer 1

1.)

Sales=c(245,138,352,322,228,275,560,366)
Advertising=c(16.5,18,22.3,17.4,19,20,32,18.6)
Commission=c(10.5,2,4,3.5,4.5,1.8,9,8.5)
data=as.data.frame(cbind(Sales,Advertising,Commission))
model1=lm(Sales~Advertising+Commission, data = data)
dat2=data.frame(Advertising=25,Commission=8)
predict(model1,dat2)

Answer: 424.6849

2.)

summary(model1)

Estimate Std. Error t value Pr(>|t|)
(Intercept) -139.633 111.792 -1.249 0.2669
Advertising 19.069 5.456 3.495 0.0174 *
Commission 10.950 8.062 1.358 0.2325

So advertising is significant at 5% level of significance as p-value for it is less than 5%