Exam 16: Time-Series Forecasting

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SCENARIO 16-4 The number of cases of merlot wine sold by a Paso Robles winery in an 8-year period follows. 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 3-year moving average is to be constructed for the wine sales.The moving average for 2006 is __________. -Referring to Scenario 16-4, a centered 3-year moving average is to be constructed for the wine sales.The moving average for 2006 is __________.

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SCENARIO 16-13 Given below is the monthly time series data for U.S.retail sales of building materials over a specific year. 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, you can reject the null hypothesis for testing the appropriateness of the second-order autoregressive model at the 5% level of significance. 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 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, you can reject the null hypothesis for testing the appropriateness of the second-order autoregressive model at the 5% level of significance. month is 0: 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, you can reject the null hypothesis for testing the appropriateness of the second-order autoregressive model at the 5% level of significance. Below is the residual plot of the various models: 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, you can reject the null hypothesis for testing the appropriateness of the second-order autoregressive model at the 5% level of significance. -Referring to Scenario 16-13, you can reject the null hypothesis for testing the appropriateness of the second-order autoregressive model at the 5% level of significance.

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SCENARIO 16-12 A local store developed a multiplicative time-series model to forecast its revenues in future quarters, using quarterly data on its revenues during the 5-year period from 2009 to 2013.The following is the resulting regression equation: SCENARIO 16-12 A local store developed a multiplicative time-series model to forecast its revenues in future quarters, using quarterly data on its revenues during the 5-year period from 2009 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 2008.   is a dummy variable equal to 1 in the first quarter of a year and 0 otherwise.   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 16-12, to obtain a forecast for the third quarter of 2014 using the model, which of the following sets of values should be used in the regression equation? where SCENARIO 16-12 A local store developed a multiplicative time-series model to forecast its revenues in future quarters, using quarterly data on its revenues during the 5-year period from 2009 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 2008.   is a dummy variable equal to 1 in the first quarter of a year and 0 otherwise.   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 16-12, to obtain a forecast for the third quarter of 2014 using the model, which of the following sets of values should be used in the regression equation? is the estimated number of contracts in a quarter. X is the coded quarterly value with X = 0 in the first quarter of 2008. SCENARIO 16-12 A local store developed a multiplicative time-series model to forecast its revenues in future quarters, using quarterly data on its revenues during the 5-year period from 2009 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 2008.   is a dummy variable equal to 1 in the first quarter of a year and 0 otherwise.   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 16-12, to obtain a forecast for the third quarter of 2014 using the model, which of the following sets of values should be used in the regression equation? is a dummy variable equal to 1 in the first quarter of a year and 0 otherwise. SCENARIO 16-12 A local store developed a multiplicative time-series model to forecast its revenues in future quarters, using quarterly data on its revenues during the 5-year period from 2009 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 2008.   is a dummy variable equal to 1 in the first quarter of a year and 0 otherwise.   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 16-12, to obtain a forecast for the third quarter of 2014 using the model, which of the following sets of values should be used in the regression equation? is a dummy variable equal to 1 in the second quarter of a year and 0 otherwise. SCENARIO 16-12 A local store developed a multiplicative time-series model to forecast its revenues in future quarters, using quarterly data on its revenues during the 5-year period from 2009 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 2008.   is a dummy variable equal to 1 in the first quarter of a year and 0 otherwise.   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 16-12, to obtain a forecast for the third quarter of 2014 using the model, which of the following sets of values should be used in the regression equation? is a dummy variable equal to 1 in the third quarter of a year and 0 otherwise. -Referring to Scenario 16-12, to obtain a forecast for the third quarter of 2014 using the model, which of the following sets of values should be used in the regression equation?

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Which of the following terms describes the overall long-term tendency of a time series?

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SCENARIO 16-7 The executive vice-president of a drug manufacturing firm believes that the demand for the firm's most popular drug has been evidencing an exponential trend since 1999.She uses Microsoft Excel to obtain the partial output below.The dependent variable is the log base 10 of the demand for the drug, while the independent variable is years, where 1999 is coded as 0, 2000 is coded as 1, etc. SUMMARY OUTPUT SCENARIO 16-7 The executive vice-president of a drug manufacturing firm believes that the demand for the firm's most popular drug has been evidencing an exponential trend since 1999.She uses Microsoft Excel to obtain the partial output below.The dependent variable is the log base 10 of the demand for the drug, while the independent variable is years, where 1999 is coded as 0, 2000 is coded as 1, etc. SUMMARY OUTPUT   -Referring to Scenario 16-7, the forecast for the demand in 2013 is __________. -Referring to Scenario 16-7, the forecast for the demand in 2013 is __________.

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Which of the following is not an advantage of exponential smoothing?

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Given a data set with 15 yearly observations, a 3-year moving average will have fewer observations than a 5-year moving average.

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SCENARIO 16-13 Given below is the monthly time series data for U.S.retail sales of building materials over a specific year. 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, the best model based on the residual plots is the quadratic-trend regression model. 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 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, the best model based on the residual plots is the quadratic-trend regression model. month is 0: 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, the best model based on the residual plots is the quadratic-trend regression model. Below is the residual plot of the various models: 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, the best model based on the residual plots is the quadratic-trend regression model. -Referring to Scenario 16-13, the best model based on the residual plots is the quadratic-trend regression model.

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Which of the following statements about the method of exponential smoothing is not true?

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SCENARIO 16-1 The number of cases of chardonnay wine sold by a Paso Robles winery in an 8-year period follows: SCENARIO 16-1 The number of cases of chardonnay wine sold by a Paso Robles winery in an 8-year period follows:   -Referring to Scenario 16-1, set up a scatter diagram (i.e., a time-series plot)with year on the horizontal X-axis. -Referring to Scenario 16-1, set up a scatter diagram (i.e., a time-series plot)with year on the horizontal X-axis.

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SCENARIO 16-13 Given below is the monthly time series data for U.S.retail sales of building materials over a specific year. 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, you can conclude that the second-order autoregressive model is appropriate at the 5% level of significance. 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 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, you can conclude that the second-order autoregressive model is appropriate at the 5% level of significance. month is 0: 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, you can conclude that the second-order autoregressive model is appropriate at the 5% level of significance. Below is the residual plot of the various models: 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, you can conclude that the second-order autoregressive model is appropriate at the 5% level of significance. -Referring to Scenario 16-13, you can conclude that the second-order autoregressive model is appropriate at the 5% level of significance.

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MAD is the summation of the residuals divided by the sample size.

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A model that can be used to make predictions about long-term future values of a time series is

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