Questions n answers rated A+
Forecasting time horizons include:
a. long range
b. medium range
c. short range
d. all of the above - correct answer ✔✔all of the above
Qualitative methods of forecasting include:
a. sales force composite
b. jury of executive opinion
c. consumer market survey
d. exponential smoothing
e. all except (d) - correct answer ✔✔all except (d)
The difference between a moving-average model and an exponential smoothing model is
that_____________. - correct answer ✔✔exponential smoothing is a weighted moving-average
model in which all prior values are weighted with a set of exponentially declining weights
Three popular measures of forecast accuracy are:
a. total error, average error, and mean error
,b. average error, median error, and maximum error
c. median error, minimum error, and maximum absolute error
d. mean absolute deviation, mean squared error, and mean absolute percent error - correct
answer ✔✔mean absolute deviation, mean squared error, and mean absolute percent error
Average demand for iPods in the Rome, Italy, Apple store is 800 units per month. The May
monthly index is 1.25. What is the seasonally adjusted sales forecast for May?
a. 640 units
b. 798.75 units
c. 800 units
d. 1,000 units
e. cannot be calculated with the information given - correct answer ✔✔1,000 units
The main difference between simple and multiple regression is __________. - correct answer
✔✔simple regression has only one independent variable
The tracking signal is the:
a. Standard error of the estimate
b. cumulative error
c. mean absolute deviation (MAD)
d. ratio of the cumulative error to MAD
e. mean absolute percent error (MAPE) - correct answer ✔✔ratio of the cumulative error to
MAD
Time-series patterns that repeat themselves after a period of days or weeks are called
__________
,a. cycles
b. seasonality
c. trends - correct answer ✔✔seasonality
Which of the following smoothing constants would make an exponential smoothing forecast
equivalent to a naïve forecast?
a. .5
b. 1.0
c. 0 - correct answer ✔✔1.0
Which of the following statements about time-series forecasting is true?
a. It is based on the assumption that the analysis of past demand helps predict future demand.
b. It is based on the assumption that future demand will be the same as past demand.
c. Because it accounts for trends, cycles, and seasonal patterns, it is always more powerful than
associative forecasting. - correct answer ✔✔It is based on the assumption that the analysis of
past demand helps predict future demand.
Which time-series model assumes that demand in the next period will be equal to the most
recent period's demand?
a. Moving average approach
b. Naïve approach
c. Exponential smoothing approach - correct answer ✔✔Naïve approach
, The degree or strength of a relationship between two variables is shown by the__________
a. mean absolute deviation
b. alpha
c. correlation coefficient - correct answer ✔✔correlation coefficient
The last four weekly values of sales were 80, 100, 105, and 90 units. The last four forecasts were
60, 80, 95, and 75 units. These forecasts illustrate:
a. Trend projections
b. Qualitative methods
c. Bias - correct answer ✔✔Bias
The primary purpose of the mean absolute deviation (MAD) in forecasting is to:
a. Seasonally adjust the forecast
b Measure forecast accuracy
c. Eliminate forecast errors - correct answer ✔✔Measure forecast accuracy
If demand is 106 during January, 120 in February, 134 in March, and 142 in April, what is the 3-
month simple moving average for May?
a. 132
b. 126
c. 138 - correct answer ✔✔132
120+134+142 = 396
396/3 = 132