Exam (elaborations) TEST BANK FOR Operations And Supply Chain Management The Core 3rd Edition Jacobs
Forecasting
True / False Questions
1. Continual
... [Show More] review and updating in light of new data is a forecasting technique
called second-guessing.
True False
2. Cyclical influences on demand are often expressed graphically as a linear
function that is either upward or downward sloping.
True False
3. Cyclical influences on demand may come from occurrences such as political
elections, war or economic conditions.
True False
4. Trend lines are usually the last things considered when developing a forecast.
True False
Operations And Supply Chain Management The Core 3rd Edition Jacobs Test Bank
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5. Time series forecasting models make predictions about the future based on
analysis of past data.
True False
6. In the weighted moving average forecasting model the weights must add up to
one times the number of data points.
True False
7. In a forecasting model using simple exponential smoothing the data pattern
should remain stationary.
True False
8. In a forecasting model using simple moving average the shorter the time span
used for calculating the moving average, the closer the average follows volatile
trends.
True False
9. In the simple exponential smoothing forecasting model you need at least 30
observations to set the smoothing constant alpha.
10. Experience and trial and error are the simplest ways to choose weights for the
weighted moving average forecasting model.
True False
11. Bayesian analysis is the simplest way to choose weights for the weighted moving
average forecasting model.
True False
12. The weighted moving average forecasting model uses a weighting scheme to
modify the effects of individual data points. This is its major advantage over the
simple moving average model.
True False
13. A central premise of exponential smoothing is that more recent data is less
indicative of the future than data from the distant past.
True False
14. The equation for exponential smoothing states that the new forecast is equal to
the old forecast plus the error of the old forecast.
True False
15. Exponential smoothing is always the best and most accurate of all forecasting
models.
True False
16. In exponential smoothing, it is desirable to use a higher smoothing constant when
forecasting demand for a product experiencing high growth.
True False
17. The value of the smoothing constant alpha in an exponential smoothing model is
between 0 and 1.
True False
18. Simple exponential smoothing lags changes in demand.
True False
19. Exponential smoothing forecasts always lag behind the actual occurrence but can
be corrected somewhat with a trend adjustment.
True False
20. Because the factors governing demand for products are very complex, all
forecasts of demand contain error.
True False
21. Random errors can be defined as those that cannot be explained by the forecast
model being used.
True False
22. There are no differences in strategic and tactical forecasting. A forecast is a
mathematical projection and its ultimate purpose should make no difference to the
analyst.
True False
23. Random errors in forecasting occur when an undetected secular trend is not
included in a forecasting model.
True False
24. When forecast errors occur in a normally distributed pattern, the ratio of the mean
absolute deviation to the standard deviation is 2 to 1, or 2 x MAD = 1 standard
deviation.
True False
25. MAD statistics can be used to generate tracking signals.
True False
26. RSFE in forecasting stands for "reliable safety function error."
True False
27. In forecasting, RSFE stands for "running sum of forecast errors."
True False
28. A tracking signal (TS) can be calculated using the arithmetic sum of forecast
deviations divided by the MAD.
True False
29. A restriction in using linear regression is that it assumes that past data and future
projections fall on or near a straight line.
True False
30. Regression is a functional relationship between two or more correlated variables,
where one variable is used to predict another.
True False
31. Linear regression is not useful for aggregate planning.
True False
32. The standard error of the estimate of a linear regression is not useful for judging
the fit between the data and the regression line when doing forecasts.
True False
33. Multiple regression analysis uses several regression models to generate a
forecast.
True False
34. For every forecasting problem there is one best forecasting technique.
True False
35. A good forecaster is one who develops special skills and experience at one
forecasting technique and is capable of applying it to widely diverse situations.
True False
36. In causal relationship forecasting leading indicators are used to forecast
occurrences.
True False
37. Qualitative forecasting techniques generally take advantage of the knowledge of
experts and therefore do not require much judgment.
True False
38. Market research is a quantitative method of forecasting.
True False
39. Decomposition of a time series means identifying and separating the time series
data into its components.
True False
40. A time series is defined in the text as chronologically ordered data that may
contain one or more components of demand variation: trend, seasonal, cyclical,
autocorrelation, and random.
True False
41. It is difficult to identify the trend in time series data.
True False
42. In decomposition of time series data it is relatively easy identify cycles and
autocorrelation components.
True False
43. We usually associate the word "seasonal" with recurrent periods of repetitive
activity that happen on other than an annual cycle.
True False
Multiple Choice Questions
44. In time series data depicting demand which of the following is not considered a
component of demand variation?
A. Trend
B. Seasonal
C. Cyclical
D. Variance
E. Autocorrelation
45. Which of the following is not one of the basic types of forecasting?
A. Qualitative
B. Time series analysis
C. Causal relationships
D. Simulation
E. Force field analysis
46. In most cases, demand for products or services can be broken down into several
components. Which of the following is not considered a component of demand?
A. Average demand for a period
B. A trend
C. Seasonal elements
D. Past data
E. Autocorrelation
47. In most cases, demand for products or services can be broken into several
components. Which of the following is considered a component of demand?
A. Cyclical elements
B. Future demand
C. Past demand
D. Inconsistent demand
E. Level demand
48. In most cases, demand for products or services can be broken into several
components. Which of the following is considered a component of demand?
A. Forecast error
B. Autocorrelation
C. Previous demand
D. Consistent demand
E. Repeat demand
49. Which of the following forecasting methodologies is considered a qualitative
forecasting technique?
A. Simple moving average
B. Market research
C. Linear regression
D. Exponential smoothing
E. Multiple regression
50. Which of the following forecasting methodologies is considered a time series
forecasting technique?
A. Simple moving average
B. Market research
C. Leading indicators
D. Historical analogy
E. Simulation
51. Which of the following forecasting methodologies is considered a time series
forecasting technique?
A. Delphi method
B. Exponential averaging
C. Simple movement smoothing
D. Weighted moving average
E. Simulation
52. Which of the following forecasting methodologies is considered a causal
forecasting technique?
A. Exponential smoothing
B. Weighted moving average
C. Linear regression
D. Historical analogy
E. Market research [Show Less]