Question

Please help me to solve part c of the question (prediction interval) by using any software "or" R "or" Minitab (whatever technology you want to use you can use to solve this part).

ent store are shown (in hundreds of thousands of dollars) in the table below for a Retail sales in quarters 1-4 over a 10-year 25.8 27.7 27.3 31.3 22.8 24.6 24.8 28.1 20.5 23.6 20.8 28.3 19.1 19.5 19.4 25 Year Quarter 1 Quarter 2 Quarter3 Quarter 4 15.6 18.6 19.9 23.7 17 18.3 15.1 21.4 12.9 16.1 13.2 21.1 13.6 12.6 11.3 16.9 11.3 12 11.6 14.8 6.7 8.7 10.8 13.9 a. Write a regression model that contains trend and seasonal components to describe the sales data. OC. 0.05 b. Use least squares regression to fit the model. Evaluate the fit of the model at What is the prediction equation? (1134) + (0.48) t+ (-449) Q1 + (-3.32) Q2 + (-455) Q3 (Round to two decimal places as needed.) Evaluate the fit of the model. Reject the null hypothesis. There is sufficient evidence to conclude that the model is useful in predicting sales C. Use the regression model to forecast the sales during quarter 2 of year 11. Give a 95% confidence interval for the forecast. The forecasted value is 28.78 (in hundreds of thousands of dollars). (Round to two decimal places as needed.) What is the 95% prediction interval? (Round to two decimal places as needed.)

Answer 1

a) the correct answer from the list is "D".

b)

The regression equation is
Y = 11.9 + 1.91 t - 5.92 Q1 - 4.28 Q2 - 5.03 Q3
c) The forcast value is 28.68.

The 95% prediction interval is (26.15, 31.21).