Could someone help show some steps for how to solve this problem? Learning alone online isn't easy.

Generate regression outputs for the following three models:

Model_X: Linear trend line forecasting

Model_Y: Seasonal forecasting without trend

Model_Z: Seasonal forecasting with trend

Answer the following questions:

a. (Refer to the Analysis of Variance section of JMP output) What is the Sum of Squared Errors for Model_X? b. The predicted sales for Quarter 1 of Year 4 (i.e., period 13) according to Model X iswhat? c. (Refer to the Analysis of Variance section of JMP output) What is the Sum of Squared Errors for Model Y? d. The predicted sales for Quarter 1 of Year 4 according to Model Y is: e. What is the Sum of Squared Errors for Model Z ? f. The predicted sales for Quarter 1 of Year 4 according to Model Z is: g. Model_X is the best fit model because it has the highest Adjusted RSquare

Trueor Fasle?

h. Model_Z is the best fit model because it has the lowest Adjusted RSquare

True or False?

O Quarterly Shampoo Sales.jmp Quarterly Shampo... Quarte Sales (millions Year r litres) 595 2 468.1 3 649.1 4 645.3 Columns (3/0) (0 00 - O U A W N - 553.9 Year 751.7 W N - Quarter 819.5 Sales (millions litres) 4 1028.4 W W W N N N N 1096 10 W N - 1278 11 1665.1 12 3 4 1703.5 Rows All rows Selected Excluded OOOON Hidden Labelled