Question 1

When forecasting with exponential smoothing,data from previous periods is _________.

Accepted Answer

A)  given equal importance 
B)  given exponentially increasing importance 
C)  ignored 
D)  given exponentially decreasing importance 
E)  linearly decreasing importance

Question 2

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 10% level 
B)  the second predictor, yt-2, is significant at the 1% 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 3

Suppose that for a time-series model,you compute a Durbin-Watson statistic D = 1.409.Assume that n = 30 and α = 0.05.Then your decision is ______.

Accepted Answer

A)  fail to reject the null hypothesis D = 0 
B)  reject the null hypothesis D = 0 
C)  fail to reject the null hypothesis ρ = 0 
D)  reject the null hypothesis ρ = 0 
E)  fail to reject the null hypothesis ρ > 0

Question 4

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

Accepted Answer

A)  yt = 3.745787 + 0.082849yt-1 + 0.035709yt-2 
B)  yt = 3.85094 + 0.70434yt-1 - 0.62669yt-2 
C)  yt = 0.84426 - 1.66023yt-1 + 14.65023yt-2 
D)  yt = 0.34299 + 0.13822yt-1 + 9.69yt-2 
E)  yt = 0.34299 + 0.13822yt-1 - 6.69yt-2

Question 5

The motivation for using an index number is to ________________.

Accepted Answer

A)  transform the data to a standard normal distribution 
B)  transform the data for a linear model 
C)  eliminate bias from the sample 
D)  reduce data to an easier-to-use, more convenient form 
E)  reduce the variance in the data

Question 6

A small value of the Durbin-Watson statistic indicates that successive error terms are positively correlated.

Accepted Answer

A) True 
 B)False

Question 7

A time series with forecast values and error terms is presented in the following table. The mean absolute deviation (MAD)for this forecast is ___________.

Accepted Answer

A)  3.54 
B)  7.41 
C)  4.43 
D)  17.72 
E)  4.34

Question 8

The forecast value for September 21.1 and the actual value turned out to be 18.Using exponential smoothing with $\alpha$ = 0.30,the forecast value for October would be ______.

Accepted Answer

A)  18.09 
B)  18.93 
C)  20.17 
D)  21.00 
E)  17.07

Question 9

The long-term general direction of data is referred to as series.

Accepted Answer

A) True 
 B)False

Question 10

Use of a smoothing constant value greater than 0.5 in an exponential smoothing model gives more weight to ___________.

Accepted Answer

A)  the actual value for the current period 
B)  the actual value for the previous period 
C)  the forecast for the current period 
D)  the forecast for the previous period 
E)  the forecast for the next period

Question 11

Calculating the "ratios of actuals to moving average" is a common step in time series decomposition. The results (the quotients)of this step estimate the ________.

Accepted Answer

A)  trend and cyclical components 
B)  seasonal and irregular components 
C)  cyclical and irregular components 
D)  trend and seasonal components 
E)  irregular components

Question 12

The city golf course is interested in starting a junior golf program.The golf pros has collected data on the number of youths under 13 that have played golf during the last 4 months.Using a three-month moving average,the forecast value for October made at the end of September in the following time series would be ____________.

Accepted Answer

A)  24 
B)  21 
C)  21.56 
D)  19.22 
E)  22

Question 13

A time series analysis was performed to determine the number of new online customers that joined the 'Jelly of the Month Club'. The actual number of new customers,the forecast values and error terms is presented in the following table.The mean absolute deviation (MAD)for this forecast is ___________.

Accepted Answer

A)  -0.50 
B)  0.50 
C)  1.50 
D)  7.00 
E)  3.00

Question 14

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 15

The forecast value for August was 22 and the actual value turned out to be 19.Using exponential smoothing with $\alpha$ = 0.30,the forecast value for September would be ______.

Accepted Answer

A)  21.1 
B)  19.9 
C)  18.1 
D)  22.9 
E)  21.0

Question 16

The forecast value for July was 210 and the actual value turned out to be 195.The researcher is using exponential smoothing and determines that the forecast value for August is 202.5.Then he is using α = ______.

Accepted Answer

A)  0.35 
B)  0.32 
C)  0.30 
D)  0.25 
E)  0.22

Question 17

Although seasonal effects can confound a trend analysis,a regression model is robust to these effects and the researcher does not need to adjust for seasonality prior to using a regression model to analyze trends.

Accepted Answer

A) True 
 B)False

Question 18

Two popular general categories of smoothing techniques are averaging models and exponential models.

Accepted Answer

A) True 
 B)False

Question 19

Using 2010 as the base year,the 2012 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

Question 20

If a researcher is using exponential smoothing and determines that the forecast for the next period (Ft + 1)is the weighted average of the actual value for the previous period (Xt)and the forecast value for the previous period (Ft),with weights of 1 and 3 respectively,then α = ______.

Accepted Answer

A)  0.25 
B)  0.33 
C)  0.67 
D)  0.75 
E)  0.90

Exam 15: Time-Series Forecasting and Index Numbers

When forecasting with exponential smoothing,data from previous periods is _________.

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

Suppose that for a time-series model,you compute a Durbin-Watson statistic D = 1.409.Assume that n = 30 and α = 0.05.Then your decision is ______.

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

The motivation for using an index number is to ________________.

A small value of the Durbin-Watson statistic indicates that successive error terms are positively correlated.

A time series with forecast values and error terms is presented in the following table. The mean absolute deviation (MAD) for this forecast is ___________.

The forecast value for September 21.1 and the actual value turned out to be 18.Using exponential smoothing with $\alpha$ = 0.30,the forecast value for October would be ______.

The long-term general direction of data is referred to as series.

Use of a smoothing constant value greater than 0.5 in an exponential smoothing model gives more weight to ___________.

Calculating the "ratios of actuals to moving average" is a common step in time series decomposition. The results (the quotients) of this step estimate the ________.

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

The forecast value for August was 22 and the actual value turned out to be 19.Using exponential smoothing with $\alpha$ = 0.30,the forecast value for September would be ______.

The forecast value for July was 210 and the actual value turned out to be 195.The researcher is using exponential smoothing and determines that the forecast value for August is 202.5.Then he is using α = ______.

Although seasonal effects can confound a trend analysis,a regression model is robust to these effects and the researcher does not need to adjust for seasonality prior to using a regression model to analyze trends.

Two popular general categories of smoothing techniques are averaging models and exponential models.

Using 2010 as the base year,the 2012 value of a simple price index for the following price data is _____________.

If a researcher is using exponential smoothing and determines that the forecast for the next period (F_{t + 1}) is the weighted average of the actual value for the previous period (X_t) and the forecast value for the previous period (F_t) ,with weights of 1 and 3 respectively,then α = ______.

Exam 15: Time-Series Forecasting and Index Numbers

When forecasting with exponential smoothing,data from previous periods is _________.

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

Suppose that for a time-series model,you compute a Durbin-Watson statistic D = 1.409.Assume that n = 30 and α = 0.05.Then your decision is ______.

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

The motivation for using an index number is to ________________.

A small value of the Durbin-Watson statistic indicates that successive error terms are positively correlated.

A time series with forecast values and error terms is presented in the following table. The mean absolute deviation (MAD) for this forecast is ___________.

The forecast value for September 21.1 and the actual value turned out to be 18.Using exponential smoothing with α\alphaα = 0.30,the forecast value for October would be ______.

The long-term general direction of data is referred to as series.

Use of a smoothing constant value greater than 0.5 in an exponential smoothing model gives more weight to ___________.

Calculating the "ratios of actuals to moving average" is a common step in time series decomposition. The results (the quotients) of this step estimate the ________.

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

The forecast value for August was 22 and the actual value turned out to be 19.Using exponential smoothing with α\alphaα = 0.30,the forecast value for September would be ______.

The forecast value for July was 210 and the actual value turned out to be 195.The researcher is using exponential smoothing and determines that the forecast value for August is 202.5.Then he is using α = ______.

Although seasonal effects can confound a trend analysis,a regression model is robust to these effects and the researcher does not need to adjust for seasonality prior to using a regression model to analyze trends.

Two popular general categories of smoothing techniques are averaging models and exponential models.

Using 2010 as the base year,the 2012 value of a simple price index for the following price data is _____________.

If a researcher is using exponential smoothing and determines that the forecast for the next period (Ft + 1) is the weighted average of the actual value for the previous period (Xt) and the forecast value for the previous period (Ft) ,with weights of 1 and 3 respectively,then α = ______.

The forecast value for September 21.1 and the actual value turned out to be 18.Using exponential smoothing with $\alpha$ = 0.30,the forecast value for October would be ______.

The forecast value for August was 22 and the actual value turned out to be 19.Using exponential smoothing with $\alpha$ = 0.30,the forecast value for September would be ______.

If a researcher is using exponential smoothing and determines that the forecast for the next period (F_{t + 1}) is the weighted average of the actual value for the previous period (X_t) and the forecast value for the previous period (F_t) ,with weights of 1 and 3 respectively,then α = ______.