Chapter Four Problems 4.23, 4.27,

4.33, and 4.35.

4.23

a) Compute MAD and MAPE for

management’s technique.

b) Do management’s results

outperform (i.e., have smaller MAD and MAPE than) a naive
forecast?

c) Which forecast do you recommend,

based on lower forecast error?

4.27″Solution available”4.33

a) Forecast the number of

transistors to be made next year, using linear
regression.

b) Compute the mean squared error

(MSE) when using linear regression.

c) Compute the mean absolute percent

error (MAPE).

4.35

a) Use the model to predict the

selling price of a house that is 1,860 square feet.

b) A 1,860-square-foot house

recently sold for $95,000. Explain why this is not what the
model predicted.

c) If you were going to use multiple

regression to develop such a model, what other quantitative
variables might you

include?

d) What

is the value of the coefficient of determination in this
problem?

Chapter Four Problems 4.23, 4.27,

4.33, and 4.35.

4.23

a) Compute MAD and MAPE for

management’s technique.

b) Do management’s results

outperform (i.e., have smaller MAD and MAPE than) a naive
forecast?

c) Which forecast do you recommend,

based on lower forecast error?

4.27″Solution available”4.33

a) Forecast the number of

transistors to be made next year, using linear
regression.

b) Compute the mean squared error

(MSE) when using linear regression.

c) Compute the mean absolute percent

error (MAPE).

4.35

a) Use the model to predict the

selling price of a house that is 1,860 square feet.

b) A 1,860-square-foot house

recently sold for $95,000. Explain why this is not what the
model predicted.

c) If you were going to use multiple

regression to develop such a model, what other quantitative
variables might you

include?

d) What

is the value of the coefficient of determination in this
problem?

Chapter Four Problems 4.23, 4.27,

4.33, and 4.35.

4.23

a) Compute MAD and MAPE for

management’s technique.

b) Do management’s results

outperform (i.e., have smaller MAD and MAPE than) a naive
forecast?

c) Which forecast do you recommend,

based on lower forecast error?

4.27″Solution available”4.33

a) Forecast the number of

transistors to be made next year, using linear
regression.

b) Compute the mean squared error

(MSE) when using linear regression.

c) Compute the mean absolute percent

error (MAPE).

4.35

a) Use the model to predict the

selling price of a house that is 1,860 square feet.

b) A 1,860-square-foot house

recently sold for $95,000. Explain why this is not what the
model predicted.

c) If you were going to use multiple

regression to develop such a model, what other quantitative
variables might you

include?

d) What

is the value of the coefficient of determination in this
problem?

4.33, and 4.35.

4.23

a) Compute MAD and MAPE for

management’s technique.

b) Do management’s results

outperform (i.e., have smaller MAD and MAPE than) a naive
forecast?

c) Which forecast do you recommend,

based on lower forecast error?

a) Forecast the number of

transistors to be made next year, using linear
regression.

b) Compute the mean squared error

(MSE) when using linear regression.

c) Compute the mean absolute percent

error (MAPE).

4.35

a) Use the model to predict the

selling price of a house that is 1,860 square feet.

recently sold for $95,000. Explain why this is not what the
model predicted.

regression to develop such a model, what other quantitative
variables might you

include?

d) What

is the value of the coefficient of determination in this
problem?