1. Refer to Exhibit 17-2. The slope of linear trend equation, b₁, is ______.
2. A method of smoothing a time series that can be used to identify the combined trend/cyclical component is the moving average
3. If the estimate of the trend component is 158.2, the estimate of the seasonal component is 94%, the estimate of the cyclical component is 105%, and the estimate of the irregular component is 98%, then the multiplicative model will produce a forecast of _____. 153.02
4. If data for a time series analysis are collected on an annual basis only, which pattern can be ignored? seasonal
5. To calculate an exponential smoothing forecast of demand, what values are required? alpha, last forecast, last actual demand
6. A qualitative forecasting method that obtains forecasts through “group consensus” is known as the ______. Delphi approach
7. Refer to Exhibit 17-5. Using a three-week moving average, what is the forecast for the first week in April? 204.33
8. Refer to Exhibit 17-3. In which time period does the value of Y_i reach 0? 5.53
9. The term “exponential smoothing” comes from ______. the exponential nature of the weighting scheme used
10. Refer to Exhibit 17-1. An estimate of the seasonal-irregular component for quarter 3 of year 1 is ______. .64
11. The forecasting method that is appropriate when the time series has no significant trend, cyclical, or seasonal effect is _____. moving averages
12. One measure of the accuracy of a forecasting model is the ______. mean absolute error
13. All of the following are true about a cyclical pattern EXCEPT it is ______. usually easier to forecast than a seasonal pattern due to less variability
14. A method that uses a weighted average of past values for arriving at smoothed time series values is known as ______. exponential smoothing
15. The forecasting model that makes use of the “least squares” method is ______. regression
16. One measure of the accuracy of a forecasting model is ______. the mean squared error
17. In situations where you need to compare forecasting methods for different time periods, the most appropriate accuracy measure is ______. mean absolute error
18. Which of the following smoothing constants would make an exponential smoothing forecast equivalent to a naive forecast? 1.0
19. Given a demand of 61, forecast of 58, and α of .3, what would the forecast for the next period be using simple exponential smoothing? 58.9
20. The time series pattern that reflects a gradual shift or movement to a relatively higher or lower level over a longer time period is called the _____. trend pattern
21. Regarding a regression model, all of the following can be negative EXCEPT the ______. coefficient of determination
22. Which of the following forecasting methods puts the least weight on the most recent time series value? exponential smoothing with α = .2
23. A group of observations measured at successive time intervals is known as a(n) _____. time series
24. The time series pattern that exists when the data fluctuate around a constant mean is the _____. horizontal pattern
25. The estimated regression equation for these data is
    Y_t = 16.23 + .52Y _t–1 + .37Y _t–2
    
    The forecasted value for time period 27 is _____. 116.95
26. Using a four-period moving average, the forecasted value for period 5 is _____. 20
27. Refer to Exhibit 17-2. The slope of linear trend equation, b₁, is ______. 2.0
28. Common types of data patterns that can be identified when examining a time series plot include all of the following EXCEPT ______. vertical
29. A component of the time series model that results in the multi-period above-trend and below-trend behavior of a time series is a(n) _____. cyclical component
30. Refer to Exhibit 17-5. Using weights of .6, .3, and .1, what is the three-week weighted moving average forecast for April, week 1? 203.50
31. The time series pattern showing an alternating sequence of points below and above the trend line lasting more than one year is the _____. cyclical pattern
32. Using exponential smoothing, the demand forecast for time period 10 equals the demand forecast for time period 9 plus ______. α times (the error in the demand forecast for time period 9)
33. Refer to Exhibit 17-2. The intercept, b₀, is ______. 2.5
34. Refer to Exhibit 17-3. In which time period does the value of Y_i reach 0? 5.53
35. The trend pattern is easy to identify by using _____. regression analysis
36. The objective of smoothing methods is to smooth out ______. random fluctuations
37. A seasonal pattern ______. can occur within a day
38. The following linear trend expression was estimated using a time series with 17 time periods.
    T_t = 129.2 + 3.8t
    The trend projection for time period 18 is _____. 197.6
39.  The term “exponential smoothing” comes from ______. the exponential nature of the weighting scheme used
40. All of the following are true about a stationary time series EXCEPT ______. there is no variability in the time series over time
41. A parameter of the exponential smoothing model that provides the weight given to the most recent time series value in the calculation of the forecast value is known as the _____. smoothing constant
42. In the linear trend equation, T = b₀ + b_1t, b₀ represents the _____. y-intercept
43. In the linear trend equation, T_t = b₀ + b₁t b₁ represents the ______. slope of the trend line
44. Refer to Exhibit 17-1. An estimate of the trend component times the cyclical component (T ₂ C _t) for quarter 3 of year 1, when a four-quarter moving average is used, is ______. 25
45. All of the following are true about time series methods EXCEPT ______. they identify a set of related independent, or explanatory, variables
46. Refer to Exhibit 17-4. What is the forecast for Friday’s sales using a three-day weighted moving average with weights of .5 (for newest), .3, and .2 (for oldest)? 893.6
47. Refer to Exhibit 17-2. The forecast for period 10 is __. 22.5
48. The seasonal index for quarter 1 is __. 1.18
49. Refer to Exhibit 17-3. The intercept, b0, is __ 8.3
50. Refer to Exhibit 17-4. What is the forecast for Friday’s sales using a three-day moving average? 888.33
51. If the smoothing constant equals .3, then the exponential smoothing forecast for time period 3 is _. 19.2
52. All of the following are true about qualitative forecasting methods EXCEPT they __. assume the pattern of the past will continue into the future
53. Refer to Exhibit 17-3. The forecast for period 10 is __. -6.7
54. The mean squared error equals 41
55. Exhibit 16-2 In a regression model involving 30 observations, the following estimated regression equation was obtained. ŷ = 170 + 34x₁ – 3x₂ + 8x₃ + 58x₄ + 3x₅ For this model, SSR = 1,740 and SST = 2,000. The value of MSR is _____. 348
56. Refer to Exhibit 17-2. The forecast for period 5 is __. 12.5
57. Refer to Exhibit 17-5. Using a five-week moving average, what is the forecast for the first week in April? 206.40

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