Ch18 - ch 18 prep questions PDF

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1. Quantitative forecasting procedures are based on the judgment of the forecaster, who uses prior experience and expertise to make forecasts. True False 2. Causal forecasting models are based on regression framework, where the variable to be forecast depends on one or more explanatory variables. True False 3. In forecasting methods, the mean square error (MSE) is computed by dividing the sum of squared residuals (errors) by the number of observations n for which the residuals are available. True False 4. Smoothing techniques are suitable for use when forecasts need to be updated frequently due to new observations that become available. True False 5. The moving average method is one of the most complex smoothing techniques used for processing time series. True False 6. The exponential smoothing method weighs all available observations in a time series equally. True False 7. The exponential trend model is attractive when the increase in the series gets larger over time. True False 8. While we use the mean square error (MSE) to compare the linear and the exponential trend models, we cannot use it to compare the linear, quadratic, and cubic trend models. True False 9. The cyclical component of a time series typically represents repetitions within a one-year period. True False 10. When the exponential trend model is used to make forecasts, it is preferable to round the estimates b0, b1 and se in the equation True False

.

11. When a time series has both trend and seasonality, moving averages can be employed to separate the effect of these two components. True False 12. The centered moving average CMA, applied in the decomposition analysis of a time series with trend and seasonality, is the average of two consecutive moving averages. True False 13.

When the decomposition model,

, is applied, forecasts are made as

where represents the estimated trend for seasonally adjusted time series for period t, and seasonal index for period t. True False

, is the

14. When the forecasting method of seasonal dummy variables is applied on a quarterly time series, four dummy variables are needed. True False 15. Non-causal forecasting models are purely time series models in the sense that the forecasts are made based only upon historical data concerning the variable of interest. True False 16. A time series is . A. any set of data recorded at the same point in time. B. a sequence of sequential observations of a variable over time. C. a set of randomly measured data points of multiple variables at the same point in time. D. any set of data collected without regard to differences in time. 17. Which of the following is an example of a time series? A. The number of daily visitors to the Niagara Falls during the month of April. B. The recorded exam scores of students in a class. C. The sales prices of single family homes sold last month in Florida. D. The current average prices of regular gasoline in different states of the U.S. 18. Which of the following is not an example of a time series? A. Hourly volume of stocks traded on the New York Stock Exchange (NYSE) on the five last trading days. B. The number of daily visitors that frequent the Statue of Liberty during the month of July. C. The monthly sales for a retailer over a five-year period. D. The current temperature in the 49 state capitals. 19. Which of the following factors refers to quantitative forecasting methods? A. Judgment of the forecaster B. A formal model for analyzing historical data C. Prior experience of the forecaster D. Expertise of the forecaster 20. Under which of the following conditions is qualitative forecasting considered attractive? A. When the forecasts have to be documented B. When the forecasts have to be independent of the forecaster's judgment C. When past data are either unavailable or are misleading D. When the forecasts can be based on reliable data 21. Which of the following is a criticism made of qualitative forecasts? A. They become the only possible forecast when past data are either not available or are misleading. B. They provide no guidance on the likely effects of changes in explanatory variables. C. They are prone to biases such as optimism and overconfidence. D. They are difficult to document. 22. In which of the following situations is the use of qualitative forecasts most appropriate? A.A marketing manager has to forecast monthly sales for the coming financial year based on the past monthly sales figures. B A TV network executive has to forecast viewership figures for a daily talk show based on historical . data from the past on a similar show on a rival network. C.An economist has to forecast credit flow resulting from a newly introduced stimulus package by the federal government. D.A country's annual rate of growth for the upcoming year has to be estimated based on the annual GDP data from the last 20 years.

23. Under which of the following conditions is qualitative forecasting considered attractive? A. When past data are either misleading or obsolete B. When the forecasts have to be documented C. When the forecasts have to be independent of the forecaster's judgment D. When the forecasts can be based on reliable data 24. Which of the following is not a criticism made of qualitative forecasts? A. They become the only possible ones when past data are either not available or are misleading. B. They are prone to biases such as optimism and overconfidence. C They do not present any explanation of the mechanism generating the values of a variable of interest, . and simply provide a method for projecting historical data. D. They provide no guidance on the likely effects of changes in explanatory variables. 25. All criteria used for selecting the best forecasting method . A. work on a regression model framework B. base their calculation on the forecaster's judgment C. base their calculations solely on known values of explanatory variables D. compare competing models on the basis of residuals 26. A time series with observed long-term upward movements in its values is said to have A. a cyclical component B. an increasing trend component C. a seasonally increasing component D. a decreasing trend component 27. Which of the following is not true of a time series with a cyclical component? A. It has wavelike fluctuations lasting from several months to several years. B. It is difficult to analyze because cycles vary in length and amplitude. C. It typically coincides with business cycles in the economy. D. It has wavelike fluctuations always lasting less than a year. 28. The method is a smoothing technique based on computing the average from a fixed number of the most recent observations. A. exponential smoothing B. moving average C. linear regression D. casual regression 29. In a moving average method, when a new observation becomes available, the new average is computed by including the new observation and A. dropping the oldest observation. B. keeping the previous m observations. C. dropping the youngest previous observation. D. keeping any previous m - 1 observations.

30. Exhibit 18.1. The past monthly demands are shown below. The naïve method, that is, the one-period moving average method, is applied to make forecasts.

Refer to Exhibit 18.1. What is the mean square error (MSE) of the forecasts? A. -1.67 B. 275.00 C. 91.67 D. 8.33 31. Exhibit 18.1. The past monthly demands are shown below. The naive method, that is, the one-period moving average method, is applied to make forecasts.

Refer to Exhibit 18.1. What is the mean absolute deviation (MAD) of the forecasts? A. -1.67 B. 25.00 C. 91.67 D. 8.33 32. Exhibit 18.1. The past monthly demands are shown below. The naïve method, that is, the one-period moving average method, is applied to make forecasts.

Refer to Exhibit 18.1. If May's demand appears to be 35, what is the residual (error) for May? A. 35 B. 0 C. 68.75 D. 6.25 33. Which of the following is true of the exponential smoothing method? A. It does not incorporate new observations into existing forecasts. B. It weighs all recent observations equally. C. It assigns exponentially decreasing weights to older observations. D. It does not use all available observations in making a forecast.

34. Which of the following is a similarity between the exponential smoothing method and the moving average method? A. Both methods give different weights to most recent observations. B. Both methods assign weights to all available observations. C. Both methods give equal weight to every observation. D. Both methods continually revise a forecast when a new observation becomes available. 35. In the exponential smoothing formula for updating the level of the series, what does α represent? A. The weighted average of the exponentially declining weights. B. The speed of decline in the weights of older observations. C. The initial value of the time series. D. The last value of the time series.

,

36. Exhibit 18.2. The following table includes the information about a monthly time series.

Refer to Exhibit 18.2. What is the forecast for May when the three-month moving average method is applied? A. 19 B. 5 C. 20 D. 21 37. Exhibit 18.2. The following table includes the information about a monthly time series.

Refer to Exhibit 18.2. When a forecast is made by the three-month moving average method, all three monthly observations used to make this forecast are treated equally in the sense that each of them has the same weight of 1/3. What is the forecast for May when the three-month weighted moving average method is applied with the weights: 1/6, 2/6, and 3/6? Assign the smallest weight to the oldest data and the largest weight to the most recent data. A. 19.00 B. 24.00 C. 18.67 D. 21.17

38. Exhibit 18.2. The following table includes the information about a monthly time series.

Refer to Exhibit 18.2. What is the forecast for May using the exponential smoothing method with α = 0.1? A. 20.796 B. 21.000 C. 20.600 D. 20.440 39. Exhibit 18.2. The following table includes the information about a monthly time series.

Refer to Exhibit 18.2. When the exponential smoothing method with α = 0.1 is applied, what is the mean square error (MSE)? A. 20.796 B. 31.2336 C. 12.6736 D. 10.41 40. Exhibit 18.2. The following table includes the information about a monthly time series.

Refer to Exhibit 18.2. When the exponential smoothing method with α = 0.1 is applied, what is the mean absolute deviation (MAD)? A. 20.796 B. 9.16 C. 3.05 D. 3.56

41. Exhibit 18.2. The following table includes the information about a monthly time series.

Refer to Exhibit 18.2. What is the forecast for May using the exponential smoothing method with α = 0.5? A. 21 B. 21.5 C. 19 D. 19.5 42. Exhibit 18.2. The following table includes the information about a monthly time series.

Refer to Exhibit 18.2. When the exponential smoothing method with α = 0.5 is applied, what is the mean square error (MSE)? A. 21.5 B. 25 C. 41 D. 13.67 43. Exhibit 18.2. The following table includes the information about a monthly time series.

Refer to Exhibit 18.2. When the exponential smoothing method with α = 0.1 is applied, what is the mean absolute deviation (MAD)? A. 21.5 B. 3.00 C. 5.00 D. 9.00

44. Exhibit 18.2. The following table includes the information about a monthly time series.

Refer to Exhibit 18.2. When the exponential smoothing method with α = 0.1 and α = 0.5 is applied, what is the speed of decline for which the mean square error (MSE) is better? What is this mean? A. α = 0.5 and MSE = 13.67 B. α = 0.1 and MSE = 13.67 C. α = 0.5 and MSE = 10.41 D. α = 0.1 and MSE = 10.41 45. Exhibit 18.2. The following table includes the information about a monthly time series.

Refer to Exhibit 18.2. When the exponential smoothing method with α = 0.1 and α = 0.5 is applied, what is the speed of decline for which the mean absolute deviation (MAD) is better? What is this mean? A. α = 0.1 and MAD = 3.05 B. α = 0.1 and MAD = 3.00 C. α = 0.5 and MAD = 3.00 D. α = 0.5 and MAD = 3.05 46. Which of the following is true of the linear trend model? A. It assigns exponentially decreasing weights to older observations. B. It is a causal forecasting model. C. It can extract a long-term upward or downward steady movement in a series. D. It is used when a series involves only random fluctuations. 47. Which of the following types of trend models will best suit a series where the value of the series changes by a fixed amount for each period? A. Cubic trend B. Linear trend C. Exponential trend D. Quadratic trend 48. Which of the following types of trend models will best suit a series where the increase in value of the series gets larger over time? A. Exponential trend B. Linear trend C. Quadratic trend D. polynomial trend

49. Which of the following formulas is used to make forecasts using the exponential trend model? A. B. C. D. . 50. In the quadratic trend model, going to be U-shaped or inverted U-shaped? A. B. C. D.

, which coefficient determines if the trend is

51. A polynomial trend model that only allows one change in the direction of a series is known as a(n) . A. exponential trend model B. linear trend model C. cubic trend model D. quadratic trend model 52. The is a trend model that allows for one change in the direction of a series. A. linear trend model B. exponential trend model C. quadratic trend model D. cubic trend model 53. In comparison with the linear trend model, which of the following is not true of the cubic trend model? A. It has always better MSE. B. Two additional variables, and , are defined in the cubic model. C. Only one change in the direction of a series can be modeled. D. It may have better or worse adjusted R2. 54. When comparing which of the following trend models is the adjusted A. Linear versus quadratic B. Linear versus cubic C. Quadratic versus cubic D. Linear versus exponential

not used?

55 Exhibit 18.3. The following table shows the annual revenues (in millions of dollars) of a pharmaceutical company over the period 1990-2011.

Excel scatterplot shown above indicates that the annual revenues have an increasing trend. Therefore, linear, exponential, quadratic and cubic models were used to fit the trend, and the following relevant information became available after applying linear regression.

Refer to Exhibit 18.3. What is a linear trend equation? A. B. C. D.

56 Exhibit 18.3. The following table shows the annual revenues (in millions of dollars) of a pharmaceutical company over the period 1990-2011.

Excel scatterplot shown above indicates that the annual revenues have an increasing trend. Therefore, linear, exponential, quadratic and cubic models were used to fit the trend, and the following relevant information became available after applying linear regression.

Refer to Exhibit 18.3. Using the linear trend equation, one can say that the predicted revenue increases by A. 642,792,000 a year. B. $604,930,000 a year. C. $60,493,000 a year. D. $6,049,300 a year.

57 Exhibit 18.3. The following table shows the annual revenues (in millions of dollars) of a pharmaceutical company over the period 1990-2011.

Excel scatterplot shown above indicates that the annual revenues have an increasing trend. Therefore, linear, exponential, quadratic and cubic models were used to fit the trend, and the following relevant information became available after applying linear regression.

Refer to Exhibit 18.3. What is the revenue forecast for 2012 found by the linear trend equation? A. About 2 billion 149 million dollars B. About 2 billion and 189 million dollars C. About 2 billion and 334 million dollars D. About 2 billion and 34 million dollars

58 Exhibit 18.3. The following table shows the annual revenues (in millions of dollars) of a pharmaceutical company over the period 1990-2011.

Excel scatterplot shown above indicates that the annual revenues have an increasing trend. Therefore, linear, exponential, quadratic and cubic models were used to fit the trend, and the following relevant information became available after applying linear regression.

Refer to Exhibit 18.3. What is an exponential trend equation? A. B. C. D.

59 Exhibit 18.3. The following table shows the annual revenues (in millions of dollars) of a pharmaceutical company over the period 1990-2011.

Excel scatterplot shown above indicates that the annual revenues have an increasing trend. Therefore, linear, exponential, quadratic and cubic models were used to fit the trend, and the following relevant information became available after applying linear regression.

Refer to Exhibit 18.3. What is a revenue forecast for 2012 found by the exponential trend equation? A. About 2 billion and 334 million dollars B. About 2 billion and 189 million dollars C. About 2 billion and 149 million dollars D. About 2 billion and 34 million dollars

60 Exhibit 18.3. The following table shows the annual revenues (in millions of dollars) of a pharmaceutical company over the period 1990-2011.

Excel scatterplot shown above indicates that the annual revenues have an increasing trend. Therefore, linear, exponential, quadratic and cubic models were used to fit the trend, and the following relevant information became available after applying linear regression.

Refer to Exhibit 18.3. When three polynomial trend equations are compared, which of them provides the best fit? A. linear B. exponential C. quadratic D. cubic

61 Exhibit 18.3. The following table shows the annual revenues (in millions of dollars) of a pharmaceutical company over the period 1990-2011.

Excel scatterplot shown above indicates that the annual revenues have an increasing trend. Therefore, linear, exponential, quadratic and cubic models were used to fit the trend, and the following relevant information became available after applying linear regression.

Refer to Exhibit 18.3. What is a revenue forecast for 2012 found by the polynomial trend equation with the best fit? A. About 2 billion and 149 million dollars B. About 2 billion and 189 million dollars C. About 2 billion and 334 million dollars D. About 2 billion and 34 million dollars

62 Exhibit 18.3. The following table shows the annual revenues (in millions of dollars) of a pharmaceutical company over the period 1990-2011.

Excel scatterplot shown above indicates that the annual revenues have an increasing trend. Therefore, linear, exponential, quadratic and cubic models were used to fit the trend, and the following relevant information became available after applying linear regression.

Refer to Exhibit 18.3. When all four trend regression equations are compared, which of them provides the best fit? A. linear B. exponential C. quadratic D. cubic

63 Exhibit 18.3. The following table shows the annual revenues (in millions of dollars) of a pharmaceutical company over the period 1990-2011.

Excel scatterplot shown above indicates that the annual revenues have an increasing trend. Therefore, linear, exponential, quadratic and cubic models were used to fit the trend, and the following relevant information became available after applying linear regression.

Refer to Exhibit 18.3. What is the revenue forecast for 2013 found by the trend regression equation with the best fit? A. About 2 billion and 512 million dollars B. About 2 billion and 95 million dollars C. About 2 billion and 248 million dollars D. About 2 billion and 290 million dollars 64. Which of the following is a centered moving average? A. The average of all moving averages in a series. B. The average of all observations of a series. C. The average of alternative moving averages in a series. D. The average of two consecutive moving averages in a series.

65. When a time series is analyzed by the model and the trend component Tt ...