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?
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?
