1. A regression equation is given by Y= 20+0.75x

where y is the fitted value (not observed data). what is the value of the residual for the (observed) data point x= 100 and y= 90?

2. data obtained from a number of women clothing stores show that there is a (linear relationship) between sales (y,in dollars) and advertising budget (x, in dollars). The regression equation was found to be y= 5000 + 7.50x . where y is the predicted sales value (in dollars) and advertising budget of 2 women. clothing stores differ by $30,000, what will be the predicted difference in their sales?

4. A regression analysis between sales (y, in $1000) and price (x, in dollars )resulted in the following equation.

y= 50,000 -Bx. where Y is the fitted sales (in $1000). The above equation implies that an increase of ___$?____ in price is associated with a decrease of ___$?____ in sales. (fill the blanks in dollars)

5. suppose the correlation coefficient between height (measured in feet) and weight (measured in pounds) is 0.40. what is the correlation coefficient between height measured in inches and weight measured in ounces? ( one foot = 12 inches, one pound= 16 ounces)