Product Calories

In Problem   12.9 on page 418, an agent for a real estate company wanted to predict the   monthly rent for apartments, based on the size of the apartment (stored in   the file Rent). Using the results of that problem    

 Rent Size   950 850   1600 1450   1200 1085   1500 1232   950 718   1700 1485   1650 1136   935 726   875 700   1150 956    1400 1100   1650 1285   2300 1985   1800 1369   1400 1175   1450 1225   1100 1245   1700 1259   1200 1150   1150 896   1600 1361   1650 1040   1200 755   800 1000   1750 1200     

 a. Determine the coefficient of   determination, r2, and interpret its meaning.  

b. determine the standard error of the   estimate, and interpret its meaning.

c. How useful do you think this   regression model is for predicting the monthly rent?   

d. Can you think of other variables that   might explain the variation in monthly rent?    

Question

The data in   the file Coffeedrink represent the calories and fat (in grams) of 16-ounce   iced coffee drinks at Dunkin’ Donuts and Starbucks:    Product Calories (X) Fat (Y)   DD Iced Mocha Latte 240 8.0   Starbucks Frap. 260 3.5   DD Coolatta 350 22.0   Starbucks Mocha Expresso 350 20.0   Starbucks Mocha Frap. 420 16.0   Starbucks Chocolate Brownie Frap. 510   22.0   Starbucks Chocolate Frap. 530 19.0     

 a. Compute and interpret the coefficient   of correlation, r.     

 b. At the 0.05 level of significance, is   there a significant linear relationship between calories and fat?