Here are the basic of the assignment:

Question 10-50

A golf club manufacturer is trying to determine how the price of a set of clubs affects the demand for clubs. The file P10_50.xlsx contains the price of a set of clubs and the monthly sales.

a)      Assume the only factor influencing monthly sales is price. Fit the following three curves to these data: linear (Y = a + bX), exponential (Y = abX), and multiplicative (Y = aXb). Which equation fits the data best?

b)      Interpret your best-fitting equation.

c)      Using the best-fitting equation, predict sales during a month in which the price is $470.

Question 12-64

Let Yt be the sales during month t (in thousands of dollars) for a photography studio, and let Pt be the price charged for portraits during month t. The data are in the file P11_45.xlsx. Use regression to fit the following model to these data:

Yt = a + b1Yt−1 + b2Pt + et

This equation indicates that last month’s sales and the current month’s price are explanatory variables. The last term, et, is an error term. a.          If the price of a portrait during month 21 is $10,

what would you predict for sales in month 21? b.      Does there appear to be a problem with

autocorrelation of the residuals?

63.

59.

Here are the basic of the assignment:

Question 10-50

A golf club manufacturer is trying to determine how the price of a set of clubs affects the demand for clubs. The file P10_50.xlsx contains the price of a set of clubs and the monthly sales.

a)      Assume the only factor influencing monthly sales is price. Fit the following three curves to these data: linear (Y = a + bX), exponential (Y = abX), and multiplicative (Y = aXb). Which equation fits the data best?

b)      Interpret your best-fitting equation.

c)      Using the best-fitting equation, predict sales during a month in which the price is $470.

Question 12-64

Let Yt be the sales during month t (in thousands of dollars) for a photography studio, and let Pt be the price charged for portraits during month t. The data are in the file P11_45.xlsx. Use regression to fit the following model to these data:

Yt = a + b1Yt−1 + b2Pt + et

This equation indicates that last month’s sales and the current month’s price are explanatory variables. The last term, et, is an error term. a.          If the price of a portrait during month 21 is $10,

what would you predict for sales in month 21? b.      Does there appear to be a problem with

autocorrelation of the residuals?

63.

59.