1. Caf Michigans manager, Gary Stark, suspects that demand for mocha latte coffees depends on the price being charged. Based on historical observations, Gary has gathered the following data, which show the numbers of those coffees sold over six different price values:

PRICE	NUMBER SOLD
$ 2.70	760
$ 3.50	510
$ 2.00	980
$ 4.20	250
$ 3.10	320
$ 4.05	480

Using these data, how many mocha latte coffees would be forecast to be sold according to simple linear regression if the price per cup were $2.80?

2. Rhonda Clark, a Slippery Rock, PA real estate developer, has devised a regression model to help determine residential housing prices in northwestern PA. The model was developed using recent sales in a particular neighborhood. The price (Y) of the house is based on the size (square footage = X) of the house. The model is:

Y = 13,473 + 37.65X

The coefficient correlation for the model is 0.63.

1. Use the model to predict the selling price of a house that is 1,860 square feet.

2. If you were going to use multiple regression to develop such a model, what other quantitative variables might you include?