Question 1

The ratios of "actuals to moving averages" (seasonal indexes)for a time series are presented in the following table as percentages:  The final (completely adjusted)estimate of the seasonal index for Q1 is ___.

Accepted Answer

A) 109.733 
B) 109.921 
C) 113.853 
D) 113.492 
E) 111.545

Question 2

Jim Royo,manager of Billings Building Supply (BBS),wants to develop a model to forecast BBS's monthly sales (in $1,000's).He selects the dollar value of residential building permits (in $10,000)as the predictor variable.An analysis of the data yielded the following tables:   
Using $\alpha$ = 0.05 the critical value of the Durbin-Watson statistic,dL, is ___.

Accepted Answer

A) 1.24 
B) 1.22 
C) 1.13 
D) 1.15 
E) 1.85

Question 3

Analysis of data for an autoregressive forecasting model produced the following tables:   The actual values of this time series,y,were 228,54,and 191 for May,June,and July,respectively.The forecast value predicted by the model for July is ___.

Accepted Answer

A) 36.91 
B) 83.67 
C) 218.71 
D) 174.41 
E) 191

Question 4

Naïve forecasting models have no useful applications because they do not take into account data trend,cyclical effects or seasonality.

Accepted Answer

A) True 
 B)False

Question 5

Test for autocorrelation using the Durbin-Watson test,overcoming it by adding independent variables and transforming variables and taking advantage of it with autoregression.

Accepted Answer

The answer of Test for autocorrelation using the Durbin-Watson test,overcoming...

Question 6

Using a three-month moving average (with weights of 5,3,and 1 for the most current value,next most current value and oldest value,respectively),the forecast value for October made at the end of September in the following time series would be ___.

Accepted Answer

A) 7.67 
B) 8 
C) 9 
D) 6.89 
E) 11

Question 7

Using 2000 as the base year,the 1990 value of the Paasche' Price Index is ___.(Quantities are averages for the student body. )

Accepted Answer

A) 80.72 
B) 162.28 
C) 240.06 
D) 50.45 
E) 30.35

Question 8

Analysis of data for an autoregressive forecasting model produced the following tables:   The results indicate that ___.

Accepted Answer

A) the first predictor,yt-1,is significant at the 5% level 
B) the second predictor,yt-2,is significant at the 5% level 
C) all predictor variables are significant at the 5% level 
D) none of the predictor variables are significant at the 5% level 
E) the overall regression model is not significant at 5% level

Question 9

A time series with forecast values and error terms is presented in the following table.The mean squared error (MSE)for this forecast is ___.

Accepted Answer

A) 13.33 
B) 17.94 
C) 89.71 
D) 22.42 
E) 32.34

Question 10

Using a three-month moving average (with weights of 6,3,and 1 for the most current value,next most current value and oldest value,respectively),the forecast value for October made at the end of September in the following time series would be___.

Accepted Answer

A) 11.60 
B) 10.00 
C) 9.67 
D) 8.60 
E) 6.11

Question 11

Analysis of data for an autoregressive forecasting model produced the following tables:   The forecasting model is ___.

Accepted Answer

A) yt = 5.745787 + 0.062849 yt-1 + 0.065709 yt-2 
B) yt = 4.85094 - 0.10434 yt-1 + 0.962669 yt-2 
C) yt = 0.84426 - 1.66023 yt-1 + 14.65023 yt-2 
D) yt = 0.40299 + 0.103822 yt-1 + 9.yt-2 
E) yt = 0.40299 + 0.103822 yt-1 - 9.yt-2

Question 12

Which of the following is not a component of time series data?

Accepted Answer

A) trend 
B) seasonal fluctuations 
C) cyclical fluctuations 
D) normal fluctuations 
E) irregular fluctuations

Question 13

Index numbers facilitate comparison of ___.

Accepted Answer

A) means 
B) data over time 
C) variances 
D) samples 
E) deviations

Question 14

Using a three-month moving average (with weights of 6,3,and 1 for the most current value,next most current value and oldest value,respectively),the forecast value for November in the following time series is ___.

Accepted Answer

A) 11.60 
B) 10.00 
C) 9.67 
D) 8.06 
E) 8.60

Question 15

Jim Royo,manager of Billings Building Supply (BBS),wants to develop a model to forecast BBS's monthly sales (in $1,000's).He selects the dollar value of residential building permits (in $10,000)as the predictor variable.An analysis of the data yielded the following tables:   
Using $\alpha$ = 0.05 the critical value of the Durbin-Watson statistic,dU, is ___.

Accepted Answer

A) 1.54 
B) 1.42 
C) 1.43 
D) 1.44 
E) 1.85

Question 16

A time series with forecast values and error terms is presented in the following table.The mean error (ME)for this forecast is ___.

Accepted Answer

A) 1.67 
B) 1.34 
C) 6.68 
D) 3.67 
E) 2.87

Question 17

Using 2006 as the base year,the 2008 value of a simple price index for the following price data is ___.

Accepted Answer

A) 77.60 
B) 114.13 
C) 160.58 
D) 99.30 
E) 100.00

Exam 15: Time-Series Forecasting and Index Numbers

The ratios of "actuals to moving averages" (seasonal indexes) for a time series are presented in the following table as percentages: The final (completely adjusted) estimate of the seasonal index for Q₁ is ___.

Analysis of data for an autoregressive forecasting model produced the following tables: The actual values of this time series,y,were 228,54,and 191 for May,June,and July,respectively.The forecast value predicted by the model for July is ___.

Naïve forecasting models have no useful applications because they do not take into account data trend,cyclical effects or seasonality.

Test for autocorrelation using the Durbin-Watson test,overcoming it by adding independent variables and transforming variables and taking advantage of it with autoregression.

Using a three-month moving average (with weights of 5,3,and 1 for the most current value,next most current value and oldest value,respectively) ,the forecast value for October made at the end of September in the following time series would be ___.

Using 2000 as the base year,the 1990 value of the Paasche' Price Index is ___.(Quantities are averages for the student body. )

Analysis of data for an autoregressive forecasting model produced the following tables: The results indicate that ___.

A time series with forecast values and error terms is presented in the following table.The mean squared error (MSE) for this forecast is ___.

Using a three-month moving average (with weights of 6,3,and 1 for the most current value,next most current value and oldest value,respectively) ,the forecast value for October made at the end of September in the following time series would be___.

Analysis of data for an autoregressive forecasting model produced the following tables: The forecasting model is ___.

Which of the following is not a component of time series data?

Index numbers facilitate comparison of ___.

Using a three-month moving average (with weights of 6,3,and 1 for the most current value,next most current value and oldest value,respectively) ,the forecast value for November in the following time series is ___.

A time series with forecast values and error terms is presented in the following table.The mean error (ME) for this forecast is ___.

Using 2006 as the base year,the 2008 value of a simple price index for the following price data is ___.

Exam 15: Time-Series Forecasting and Index Numbers

The ratios of "actuals to moving averages" (seasonal indexes) for a time series are presented in the following table as percentages: The final (completely adjusted) estimate of the seasonal index for Q1 is ___.

Analysis of data for an autoregressive forecasting model produced the following tables: The actual values of this time series,y,were 228,54,and 191 for May,June,and July,respectively.The forecast value predicted by the model for July is ___.

Naïve forecasting models have no useful applications because they do not take into account data trend,cyclical effects or seasonality.

Test for autocorrelation using the Durbin-Watson test,overcoming it by adding independent variables and transforming variables and taking advantage of it with autoregression.

Using a three-month moving average (with weights of 5,3,and 1 for the most current value,next most current value and oldest value,respectively) ,the forecast value for October made at the end of September in the following time series would be ___.

Using 2000 as the base year,the 1990 value of the Paasche' Price Index is ___.(Quantities are averages for the student body. )

Analysis of data for an autoregressive forecasting model produced the following tables: The results indicate that ___.

A time series with forecast values and error terms is presented in the following table.The mean squared error (MSE) for this forecast is ___.

Using a three-month moving average (with weights of 6,3,and 1 for the most current value,next most current value and oldest value,respectively) ,the forecast value for October made at the end of September in the following time series would be___.

Analysis of data for an autoregressive forecasting model produced the following tables: The forecasting model is ___.

Which of the following is not a component of time series data?

Index numbers facilitate comparison of ___.

Using a three-month moving average (with weights of 6,3,and 1 for the most current value,next most current value and oldest value,respectively) ,the forecast value for November in the following time series is ___.

A time series with forecast values and error terms is presented in the following table.The mean error (ME) for this forecast is ___.

Using 2006 as the base year,the 2008 value of a simple price index for the following price data is ___.

The ratios of "actuals to moving averages" (seasonal indexes) for a time series are presented in the following table as percentages: The final (completely adjusted) estimate of the seasonal index for Q₁ is ___.