Author Question: The mean absolute error, mean squared error, and mean absolute percentage error are all methods to ... (Read 122 times)

Kthamas · **on:** Jun 24, 2018

The mean absolute error, mean squared error, and mean absolute percentage error are all methods to measure the accuracy of a forecast.These methods measure forecast accuracy by
a. determining how well a particular forecasting method is able to reproduce the time series data that are already available.
b. using the current value to estimate how well the model generates previous values correctly.
c. predicting the future values and wait for a pre-defined time period to examine how accurate the predictions were.
d. adjusting the scale of the data.

Question 2

To generate a scatter chart matrix, we use
a. native Excel functionality. b. Excel Add-In XLMiner.
c. Excel Add-In MegaStat. d. all of these.

jennafosdick · **Reply #1 on:** Jun 24, 2018

Answer to Question 1

a
RATIONALE: These measures of forecast accuracy are used to determine how well a particular forecasting method is able to reproduce the time series data that are already available. By selecting the method that is most accurate for the data already known, we hope to increase the likelihood that we will obtain more accurate forecasts for future time periods.

Answer to Question 2

b
RATIONALE: It is not possible to generate a scatter chart matrix using native Excel functionality. A scatter chart matrix is generated using the Excel Add-In XLMiner.