Exam 16: Time-Series Forecasting

SCENARIO 16-14 A contractor developed a multiplicative time-series model to forecast the number of contracts in future quarters, using quarterly data on number of contracts during the 3-year period from 2011 to 2013.The following is the resulting regression equation: where is the estimated number of contracts in a quarter. X is the coded quarterly value with X = 0 in the first quarter of 2011. is a dummy variable equal to 1 in the first quarter of a year and 0 otherwise. Q is a dummy variable equal to 1 in the second quarter of a year and 0 otherwise. is a dummy variable equal to 1 in the third quarter of a year and 0 otherwise. -Referring to Scenario 16-14, using the regression equation, which of the following values is the best forecast for the number of contracts in the second quarter of 2015?

SCENARIO 16-10 Business closures in a city in the western U.S.from 2007 to 2012 were: Microsoft Excel was used to fit both first-order and second-order autoregressive models, resulting in the following partial outputs: -Referring to Scenario 16-10, the residuals for the second-order autoregressive model are ________, ________, ________, and ________.

SCENARIO 16-13 Given below is the monthly time series data for U.S.retail sales of building materials over a specific year. The results of the linear trend, quadratic trend, exponential trend, first-order autoregressive, second-order autoregressive and third-order autoregressive model are presented below in which the coded month for the month is 0: Below is the residual plot of the various models: -Referring to Scenario 16-13, what is your forecast for the month using the second- order autoregressive model?

SCENARIO 16-13 Given below is the monthly time series data for U.S.retail sales of building materials over a specific year. The results of the linear trend, quadratic trend, exponential trend, first-order autoregressive, second-order autoregressive and third-order autoregressive model are presented below in which the coded month for the month is 0: Below is the residual plot of the various models: -Referring to Scenario 16-13, what is your forecast for the month using the linear-trend model?

Which of the following terms describes the up and down movements of a time series that vary both in length and intensity?

SCENARIO 16-14 A contractor developed a multiplicative time-series model to forecast the number of contracts in future quarters, using quarterly data on number of contracts during the 3-year period from 2011 to 2013.The following is the resulting regression equation: where is the estimated number of contracts in a quarter. X is the coded quarterly value with X = 0 in the first quarter of 2011. is a dummy variable equal to 1 in the first quarter of a year and 0 otherwise. Q is a dummy variable equal to 1 in the second quarter of a year and 0 otherwise. is a dummy variable equal to 1 in the third quarter of a year and 0 otherwise. -Referring to Scenario 16-14, the best interpretation of the coefficient of X (0.117)in the regression equation is:

SCENARIO 16-14 A contractor developed a multiplicative time-series model to forecast the number of contracts in future quarters, using quarterly data on number of contracts during the 3-year period from 2011 to 2013.The following is the resulting regression equation: where is the estimated number of contracts in a quarter. X is the coded quarterly value with X = 0 in the first quarter of 2011. is a dummy variable equal to 1 in the first quarter of a year and 0 otherwise. Q is a dummy variable equal to 1 in the second quarter of a year and 0 otherwise. is a dummy variable equal to 1 in the third quarter of a year and 0 otherwise. -Referring to Scenario 16-14, to obtain a forecast for the first quarter of 2014 using the model, which of the following sets of values should be used in the regression equation?

SCENARIO 16-5 The number of passengers arriving at San Francisco on the Amtrak cross-country express on 6 successive Mondays were: 60, 72, 96, 84, 36, and 48. -Referring to Scenario 16-5, the number of arrivals will be exponentially smoothed with a smoothing constant of 0.25.The smoothed value for the second Monday will be __________.

SCENARIO 16-4 The number of cases of merlot wine sold by a Paso Robles winery in an 8-year period follows. -Referring to Scenario 16-4, construct a centered 5-year moving average for the wine sales.

The effect of an unpredictable, rare event will be contained in the ___________ component.

SCENARIO 16-13 Given below is the monthly time series data for U.S.retail sales of building materials over a specific year. The results of the linear trend, quadratic trend, exponential trend, first-order autoregressive, second-order autoregressive and third-order autoregressive model are presented below in which the coded month for the month is 0: Below is the residual plot of the various models: -Referring to Scenario 16-13, what is the exponentially smoothed forecast for the 1 month using a smoothing coefficient of W = 0.25 if the exponentially smooth value for the 1 and month are 9,477.7776 and 9,411.8332, respectively?

SCENARIO 16-5 The number of passengers arriving at San Francisco on the Amtrak cross-country express on 6 successive Mondays were: 60, 72, 96, 84, 36, and 48. -Referring to Scenario 16-5, the number of arrivals will be exponentially smoothed with a smoothing constant of 0.1.Then the forecast for the seventh Monday will be __________.

SCENARIO 16-13 Given below is the monthly time series data for U.S.retail sales of building materials over a specific year. The results of the linear trend, quadratic trend, exponential trend, first-order autoregressive, second-order autoregressive and third-order autoregressive model are presented below in which the coded month for the month is 0: Below is the residual plot of the various models: -Referring to Scenario 16-13, construct a scatter plot (i.e., a time-series plot)with month on the horizontal X-axis.

SCENARIO 16-4 The number of cases of merlot wine sold by a Paso Robles winery in an 8-year period follows. -Referring to Scenario 16-4, a centered 5-year moving average is to be constructed for the wine sales.The moving average for 2007 is __________.

SCENARIO 16-6 The president of a chain of department stores believes that her stores' total sales have been showing a linear trend since 1993.She uses Microsoft Excel to obtain the partial output below. The dependent variable is sales (in millions of dollars), while the independent variable is coded years, where 1993 is coded as 0, 1994 is coded as 1, etc. SUMMARY OUTPUT -Referring to Scenario 16-6, the estimate of the amount by which sales (in millions of dollars)is increasing each year is __________.

SCENARIO 16-3 The following table contains the number of complaints received in a department store for the first 6 months of last year. -Referring to Scenario 16-3, suppose the last two smoothed values are 81 and 96 (Note: they are not).What would you forecast as the value of the time series for September?

SCENARIO 16-5 The number of passengers arriving at San Francisco on the Amtrak cross-country express on 6 successive Mondays were: 60, 72, 96, 84, 36, and 48. -Referring to Scenario 16-5, the number of arrivals will be smoothed with a 3-term moving average.There will be a total of __________ smoothed values.

The method of least squares is used on time-series data for

SCENARIO 16-4 The number of cases of merlot wine sold by a Paso Robles winery in an 8-year period follows. -Referring to Scenario 16-4, exponentially smooth the wine sales with a weight or smoothing constant of 0.2.

SCENARIO 16-8 The manager of a marketing consulting firm has been examining his company's yearly profits. He believes that these profits have been showing a quadratic trend since 1994.He uses Microsoft Excel to obtain the partial output below.The dependent variable is profit (in thousands of dollars), while the independent variables are coded years and squared of coded years, where 1994 is coded as 0, 1995 is coded as 1, etc. SUMMARY OUTPUT -Referring to Scenario 16-8, the forecast for profits in 2019 is __________.