Deck 15: Time-Series Forecasting and Index Numbers

ملء الشاشة (f)
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سؤال
When the error terms of a regression forecasting model are correlated the problem of autocorrelation occurs.
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سؤال
A stationary time-series data has only trend but no cyclical or seasonal effects.
سؤال
Naïve forecasting models have no useful applications because they do not take into account data trend,cyclical effects or seasonality.
سؤال
If autocorrelation occurs in regression analysis,then the confidence intervals and tests using the t and F distributions are no longer strictly applicable.
سؤال
Time-series data are data gathered on a desired characteristic at a particular point in time.
سؤال
Two popular general categories of smoothing techniques are averaging models and exponential models.
سؤال
If the trend equation is quadratic in time t=1….T,the forecast value for the next time T+1 depends on time T.
سؤال
For large datasets,the mean error (ME)and mean absolute deviation (MAD)always have the same numerical value.
سؤال
Linear regression models cannot be used to analyze quadratic trends in time-series data.
سؤال
When a trucking firm uses the number of shipments for January of the previous year as the forecast for January next year,it is using a naïve forecasting model.
سؤال
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.
سؤال
Forecast error is the difference between the value of the response variable and those of the explanatory variables.
سؤال
Two popular general categories of smoothing techniques are exponential models and logarithmic models.
سؤال
One of the ways to overcome the autocorrelation problem in a regression forecasting model is to increase the level of significance for the F test
سؤال
If the trend equation is linear in time,the slope indicates the increase,or decrease when negative,in the forecasted value of the response value Y for the next time period.
سؤال
One of the ways to overcome the autocorrelation problem in a regression forecasting model is to transform the variables by taking the first-differences.
سؤال
One of the main techniques for isolating the effects of seasonality is decomposition.
سؤال
The long-term general direction of data is referred to as series.
سؤال
One of the main techniques for isolating the effects of seasonality is reconstitution.
سؤال
An exponential smoothing technique in which the smoothing constant alpha is equal to one is equivalent to a regression forecasting model.
سؤال
In exponential smoothing models,the value of the smoothing constant may be any number between ___________.

A)-1 and 1
B)-5 and 5
C)0 and 1
D)0 and 10
E)0 and 100
سؤال
A time series with forecast values and error terms is presented in the following table.The mean squared error (MSE)for this forecast is ___________. <strong>A time series with forecast values and error terms is presented in the following table.The mean squared error (MSE)for this forecast is ___________.  </strong> A)13.33 B)17.94 C)89.71 D)22.43 E)32.34 <div style=padding-top: 35px>

A)13.33
B)17.94
C)89.71
D)22.43
E)32.34
سؤال
Use of a smoothing constant value less than 0.5 in an exponential smoothing model gives more weight to ___________.

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
سؤال
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 error (ME)for this forecast is ___________. <strong>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 error (ME)for this forecast is ___________.  </strong> A)-0.50 B)0.50 C)1.50 D)7.00 E)3.00 <div style=padding-top: 35px>

A)-0.50
B)0.50
C)1.50
D)7.00
E)3.00
سؤال
A small value of the Durbin-Watson statistic indicates that successive error terms are positively correlated.
سؤال
Using a three-month moving average,the forecast value for November in the following time series is ____________. <strong>Using a three-month moving average,the forecast value for November in the following time series is ____________.  </strong> A)11.60 B)10.00 C)9.67 D)8.60 E)6.00 <div style=padding-top: 35px>

A)11.60
B)10.00
C)9.67
D)8.60
E)6.00
سؤال
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__________. <strong>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__________.  </strong> A)11.60 B)10.00 C)9.67 D)8.60 E)6.11 <div style=padding-top: 35px>

A)11.60
B)10.00
C)9.67
D)8.60
E)6.11
سؤال
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 ____________. <strong>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 ____________.  </strong> A)24 B)21 C)21.56 D)19.22 E)22 <div style=padding-top: 35px>

A)24
B)21
C)21.56
D)19.22
E)22
سؤال
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 ____________. <strong>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 ____________.  </strong> A)11.60 B)10.00 C)9.67 D)8.06 E)8.60 <div style=padding-top: 35px>

A)11.60
B)10.00
C)9.67
D)8.06
E)8.60
سؤال
Using a three-month moving average,the forecast value for October made at the end of September in the following time series would be ____________. <strong>Using a three-month moving average,the forecast value for October made at the end of September in the following time series would be ____________.  </strong> A)11.60 B)10.00 C)9.07 D)8.06 E)9.67 <div style=padding-top: 35px>

A)11.60
B)10.00
C)9.07
D)8.06
E)9.67
سؤال
Unweighted price indexes compare across the entire time period for which there is data.
سؤال
The city golf course is interested in starting a junior golf program.The golf pro 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 November in the following time series would be ____________. <strong>The city golf course is interested in starting a junior golf program.The golf pro 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 November in the following time series would be ____________.  </strong> A)24 B)21 C)21.56 D)19.22 E)22 <div style=padding-top: 35px>

A)24
B)21
C)21.56
D)19.22
E)22
سؤال
Use of a smoothing constant value greater than 0.5 in an exponential smoothing model gives more weight to ___________.

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

A)given equal importance
B)given exponentially increasing importance
C)ignored
D)given exponentially decreasing importance
E)linearly decreasing importance
سؤال
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 squared error (MSE)for this forecast is ___________. <strong>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 squared error (MSE)for this forecast is ___________.  </strong> A)-0.50 B)0.50 C)1.50 D)7.00 E)3.00 <div style=padding-top: 35px>

A)-0.50
B)0.50
C)1.50
D)7.00
E)3.00
سؤال
A time series with forecast values and error terms is presented in the following table.The mean absolute deviation (MAD)for this forecast is ___________. <strong>A time series with forecast values and error terms is presented in the following table.The mean absolute deviation (MAD)for this forecast is ___________.  </strong> A)3.54 B)7.41 C)4.43 D)17.72 E)4.34 <div style=padding-top: 35px>

A)3.54
B)7.41
C)4.43
D)17.72
E)4.34
سؤال
In statistics,the Winters' Three Parameter statistic is a test statistic used to detect the presence of autocorrelation in the residuals from a regression analysis.
سؤال
Autocorrelation in a regression forecasting model can be detected by the F test.
سؤال
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 ___________. <strong>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 ___________.  </strong> A)-0.50 B)0.50 C)1.50 D)7.00 E)3.00 <div style=padding-top: 35px>

A)-0.50
B)0.50
C)1.50
D)7.00
E)3.00
سؤال
A time series with forecast values and error terms is presented in the following table.The mean error (ME)for this forecast is ___________. <strong>A time series with forecast values and error terms is presented in the following table.The mean error (ME)for this forecast is ___________.  </strong> A)1.67 B)1.34 C)6.68 D)3.67 E)2.87 <div style=padding-top: 35px>

A)1.67
B)1.34
C)6.68
D)3.67
E)2.87
سؤال
Analysis of data for an autoregressive forecasting model produced the following tables. <strong>Analysis of data for an autoregressive forecasting model produced the following tables.     The results indicate that __________.</strong> 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 <div style=padding-top: 35px> <strong>Analysis of data for an autoregressive forecasting model produced the following tables.     The results indicate that __________.</strong> 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 <div style=padding-top: 35px> The results indicate that __________.

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
سؤال
The ratios of "actuals to moving averages" (seasonal indexes)for a time series are presented in the following table as percentages. <strong>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 __________.</strong> A)109.733 B)109.921 C)113.853 D)113.492 E)111.545 <div style=padding-top: 35px> The final (completely adjusted)estimate of the seasonal index for Q1 is __________.

A)109.733
B)109.921
C)113.853
D)113.492
E)111.545
سؤال
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)trend and cyclical components
B)seasonal and irregular components
C)cyclical and irregular components
D)trend and seasonal components
E)irregular components
سؤال
Which of the following is not a component of time series data?

A)Trend
B)Seasonal fluctuations
C)Cyclical fluctuations
D)Normal fluctuations
E)Irregular fluctuations
سؤال
Analysis of data for an autoregressive forecasting model produced the following tables. <strong>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 predicted (forecast)value for August is __________.</strong> A)-101.00 B)104.54 C)218.71 D)21.56 E)-77.81 <div style=padding-top: 35px> <strong>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 predicted (forecast)value for August is __________.</strong> A)-101.00 B)104.54 C)218.71 D)21.56 E)-77.81 <div style=padding-top: 35px> The actual values of this time series,y,were 228,54,and 191 for May,June,and July,respectively.The predicted (forecast)value for August is __________.

A)-101.00
B)104.54
C)218.71
D)21.56
E)-77.81
سؤال
The city golf course is interested in starting a junior golf program.The golf pro 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 (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 __________. <strong>The city golf course is interested in starting a junior golf program.The golf pro 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 (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 __________.  </strong> A)24 B)21 C)21.56 D)19.22 E)22 <div style=padding-top: 35px>

A)24
B)21
C)21.56
D)19.22
E)22
سؤال
The following graph of a time-series data suggests a _______________ trend.

A)linear <strong>The following graph of a time-series data suggests a _______________ trend.</strong> A)linear   B)tangential C)cosine D)quadratic E)flat <div style=padding-top: 35px>
B)tangential
C)cosine
D)quadratic
E)flat
سؤال
The following graph of time-series data suggests a _______________ trend. <strong>The following graph of time-series data suggests a _______________ trend.    </strong> A)linear B)quadratic C)cosine D)tangential E)flat <div style=padding-top: 35px> <strong>The following graph of time-series data suggests a _______________ trend.    </strong> A)linear B)quadratic C)cosine D)tangential E)flat <div style=padding-top: 35px>

A)linear
B)quadratic
C)cosine
D)tangential
E)flat
سؤال
Fitting a linear trend to 36 monthly data points (January 2011 = 1,February 2011 =2,March 2011 = 3,etc.)produced the following tables. <strong>Fitting a linear trend to 36 monthly data points (January 2011 = 1,February 2011 =2,March 2011 = 3,etc.)produced the following tables.     The projected trend value for January 2014 is ________.</strong> A)544.29 B)868.61 C)652.39 D)760.50 E)876.90 <div style=padding-top: 35px> <strong>Fitting a linear trend to 36 monthly data points (January 2011 = 1,February 2011 =2,March 2011 = 3,etc.)produced the following tables.     The projected trend value for January 2014 is ________.</strong> A)544.29 B)868.61 C)652.39 D)760.50 E)876.90 <div style=padding-top: 35px> The projected trend value for January 2014 is ________.

A)544.29
B)868.61
C)652.39
D)760.50
E)876.90
سؤال
In an autoregressive forecasting model,the independent variable(s)is (are)______.

A)time-lagged values of the dependent variable
B)first-order differences of the dependent variable
C)second-order,or higher,differences of the dependent variable
D)first-order quotients of the dependent variable
E)time-lagged values of the independent variable
سؤال
Analysis of data for an autoregressive forecasting model produced the following tables. <strong>Analysis of data for an autoregressive forecasting model produced the following tables.     The forecasting model is __________.</strong> 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 <div style=padding-top: 35px> <strong>Analysis of data for an autoregressive forecasting model produced the following tables.     The forecasting model is __________.</strong> 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 <div style=padding-top: 35px> The forecasting model is __________.

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
سؤال
Fitting a linear trend to 36 monthly data points (January 2011 = 1,February 2011 =2,March 2011 = 3,etc.)produced the following tables. <strong>Fitting a linear trend to 36 monthly data points (January 2011 = 1,February 2011 =2,March 2011 = 3,etc.)produced the following tables.     The projected trend value for January 2014 is ________.</strong> A)231.39 B)555.71 C)339.50 D)447.76 E)355.71 <div style=padding-top: 35px> <strong>Fitting a linear trend to 36 monthly data points (January 2011 = 1,February 2011 =2,March 2011 = 3,etc.)produced the following tables.     The projected trend value for January 2014 is ________.</strong> A)231.39 B)555.71 C)339.50 D)447.76 E)355.71 <div style=padding-top: 35px> The projected trend value for January 2014 is ________.

A)231.39
B)555.71
C)339.50
D)447.76
E)355.71
سؤال
The high and low values of the "ratios of actuals to moving average" are ignored when finalizing the seasonal index for a period (month or quarter)in time series decomposition.The rationale for this is to ________.

A)reduce the sample size
B)eliminate autocorrelation
C)minimize serial correlation
D)eliminate the irregular component
E)eliminate the trend
سؤال
The city golf course is interested in starting a junior golf program.The golf pro 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 (with weights of 5,3,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 would be ____________. <strong>The city golf course is interested in starting a junior golf program.The golf pro 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 (with weights of 5,3,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 would be ____________.  </strong> A)24 B)21 C)21.56 D)19.22 E)22 <div style=padding-top: 35px>

A)24
B)21
C)21.56
D)19.22
E)22
سؤال
What is the forecast for the Period 7 using a 3-period moving average technique,given the following time-series data for six past periods? <strong>What is the forecast for the Period 7 using a 3-period moving average technique,given the following time-series data for six past periods?  </strong> A)164.67 B)156.00 C)148.00 D)126.57 E)158.67 <div style=padding-top: 35px>

A)164.67
B)156.00
C)148.00
D)126.57
E)158.67
سؤال
The forecast value for August was 22 and the actual value turned out to be 19.Using exponential smoothing with α\alpha = 0.30,the forecast value for September would be ______.

A)21.1
B)19.9
C)18.1
D)22.9
E)21.0
سؤال
The following graph of a time-series data suggests a _______________ trend.

A)linear <strong>The following graph of a time-series data suggests a _______________ trend.</strong> A)linear   B)quadratic C)cosine D)tangential E)flat <div style=padding-top: 35px>
B)quadratic
C)cosine
D)tangential
E)flat
سؤال
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.  <strong>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 _________.</strong> A)1.24 B)1.22 C)1.13 D)1.15 E)1.85 <div style=padding-top: 35px>   <strong>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 _________.</strong> A)1.24 B)1.22 C)1.13 D)1.15 E)1.85 <div style=padding-top: 35px>
Using α\alpha = 0.05 the critical value of the Durbin-Watson statistic,dL,is _________.

A)1.24
B)1.22
C)1.13
D)1.15
E)1.85
سؤال
Analysis of data for an autoregressive forecasting model produced the following tables. <strong>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 __________.</strong> A)-101.00 B)104.54 C)218.71 D)21.56 E)-77.81 <div style=padding-top: 35px> <strong>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 __________.</strong> A)-101.00 B)104.54 C)218.71 D)21.56 E)-77.81 <div style=padding-top: 35px> 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 __________.

A)-101.00
B)104.54
C)218.71
D)21.56
E)-77.81
سؤال
The forecast value for September 21.1 and the actual value turned out to be 18.Using exponential smoothing with α\alpha = 0.30,the forecast value for October would be ______.

A)18.09
B)18.93
C)20.17
D)21.00
E)17.07
سؤال
A weighted aggregate price index where the weight for each item is computed by using the quantities of the base period is known as the a.Paasche Index
B.Simple Index
C.Laspeyres Index
D.Consumer Price index
E.Producer Price index
سؤال
The motivation for using an index number is to ________________.

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
سؤال
Index numbers facilitate comparison of ____________.

A)means
B)data over time
C)variances
D)samples
E)deviations
سؤال
Using 2000 as the base year,the 1990 value of the Paasche' Price Index is ______.(Quantities are averages for the student body.) <strong>Using 2000 as the base year,the 1990 value of the Paasche' Price Index is ______.(Quantities are averages for the student body.)  </strong> A)80.72 B)162.28 C)240.06 D)50.45 E)30.35 <div style=padding-top: 35px>

A)80.72
B)162.28
C)240.06
D)50.45
E)30.35
سؤال
Using 2011 as the base year,the 2010 value of the Paasche' Price Index is ______. <strong>Using 2011 as the base year,the 2010 value of the Paasche' Price Index is ______.  </strong> A)99.79 B)192.51 C)100.29 D)59.19 E)39.99 <div style=padding-top: 35px>

A)99.79
B)192.51
C)100.29
D)59.19
E)39.99
سؤال
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.  <strong>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 _________.</strong> A)1.54 B)1.42 C)1.43 D)1.44 E)1.85 <div style=padding-top: 35px>   <strong>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 _________.</strong> A)1.54 B)1.42 C)1.43 D)1.44 E)1.85 <div style=padding-top: 35px>
Using α\alpha = 0.05 the critical value of the Durbin-Watson statistic,dU,is _________.

A)1.54
B)1.42
C)1.43
D)1.44
E)1.85
سؤال
When constructing a weighted aggregate price index,the weights usually are _____.

A)prices of substitute items
B)prices of complementary items
C)quantities of the respective items
D)squared quantities of the respective items
E)quality of individual items
سؤال
Typically,the denominator used to calculate an index number is a measurement for the ____________ period.

A)base
B)current
C)spanning
D)intermediate
E)peak
سؤال
Weighted aggregate price indexes are also known as _______.

A)unbalanced indexes
B)balanced indexes
C)value indexes
D)multiplicative indexes
E)overall indexes
سؤال
Using 2011 as the base year,the 2010 value of the Laspeyres Price Index is ______. <strong>Using 2011 as the base year,the 2010 value of the Laspeyres Price Index is ______.  </strong> A)69.92 B)144.06 C)100.21 D)79.72 E)99.72 <div style=padding-top: 35px>

A)69.92
B)144.06
C)100.21
D)79.72
E)99.72
سؤال
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.  <strong>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.     Jim's calculated value for the Durbin-Watson statistic is 1.14.Using  \alpha = 0.05,the appropriate decision is: _________.</strong> A)do not reject H0:  \rho  = 0 B)reject H0:  \rho  = 0 C)do not reject H0:  \rho   \neq  0 D)the test is inconclusive E)reject H0:  \rho  ≠ 0 <div style=padding-top: 35px>   <strong>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.     Jim's calculated value for the Durbin-Watson statistic is 1.14.Using  \alpha = 0.05,the appropriate decision is: _________.</strong> A)do not reject H0:  \rho  = 0 B)reject H0:  \rho  = 0 C)do not reject H0:  \rho   \neq  0 D)the test is inconclusive E)reject H0:  \rho  ≠ 0 <div style=padding-top: 35px>
Jim's calculated value for the Durbin-Watson statistic is 1.14.Using α\alpha = 0.05,the appropriate decision is: _________.

A)do not reject H0: ρ\rho = 0
B)reject H0: ρ\rho = 0
C)do not reject H0: ρ\rho \neq 0
D)the test is inconclusive
E)reject H0: ρ\rho ≠ 0
سؤال
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.  <strong>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.     Jim's calculated value for the Durbin-Watson statistic is 1.93.Using  \alpha = 0.05,the appropriate decision is: _________.</strong> A)do not reject H0:  \rho  = 0 B)reject H0: \rho  ≠ 0 C)do not reject:  \rho   \neq  0 D)the test is inconclusive E)reject H0:  \rho  = 0 <div style=padding-top: 35px>   <strong>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.     Jim's calculated value for the Durbin-Watson statistic is 1.93.Using  \alpha = 0.05,the appropriate decision is: _________.</strong> A)do not reject H0:  \rho  = 0 B)reject H0: \rho  ≠ 0 C)do not reject:  \rho   \neq  0 D)the test is inconclusive E)reject H0:  \rho  = 0 <div style=padding-top: 35px>
Jim's calculated value for the Durbin-Watson statistic is 1.93.Using α\alpha = 0.05,the appropriate decision is: _________.

A)do not reject H0: ρ\rho = 0
B)reject H0: ρ\rho ≠ 0
C)do not reject: ρ\rho \neq 0
D)the test is inconclusive
E)reject H0: ρ\rho = 0
سؤال
A weighted aggregate price index where the weight for each item is computed by using the quantities of the year of interest is known as the a.Paasche Index
B.Simple Index
C.Laspeyres Index
D.Consumer Price index
E.Producer Price index
سؤال
Often,index numbers are expressed as ____________.

A)percentages
B)frequencies
C)cycles
D)regression coefficients
E)correlation coefficients
سؤال
Using 2010 as the base year,the 2012 value of a simple price index for the following price data is _____________. <strong>Using 2010 as the base year,the 2012 value of a simple price index for the following price data is _____________.  </strong> A)77.60 B)114.13 C)160.58 D)99.30 E)100.00 <div style=padding-top: 35px>

A)77.60
B)114.13
C)160.58
D)99.30
E)100.00
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Deck 15: Time-Series Forecasting and Index Numbers
1
When the error terms of a regression forecasting model are correlated the problem of autocorrelation occurs.
True
2
A stationary time-series data has only trend but no cyclical or seasonal effects.
False
3
Naïve forecasting models have no useful applications because they do not take into account data trend,cyclical effects or seasonality.
False
4
If autocorrelation occurs in regression analysis,then the confidence intervals and tests using the t and F distributions are no longer strictly applicable.
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5
Time-series data are data gathered on a desired characteristic at a particular point in time.
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6
Two popular general categories of smoothing techniques are averaging models and exponential models.
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7
If the trend equation is quadratic in time t=1….T,the forecast value for the next time T+1 depends on time T.
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8
For large datasets,the mean error (ME)and mean absolute deviation (MAD)always have the same numerical value.
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9
Linear regression models cannot be used to analyze quadratic trends in time-series data.
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10
When a trucking firm uses the number of shipments for January of the previous year as the forecast for January next year,it is using a naïve forecasting model.
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11
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.
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12
Forecast error is the difference between the value of the response variable and those of the explanatory variables.
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13
Two popular general categories of smoothing techniques are exponential models and logarithmic models.
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14
One of the ways to overcome the autocorrelation problem in a regression forecasting model is to increase the level of significance for the F test
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15
If the trend equation is linear in time,the slope indicates the increase,or decrease when negative,in the forecasted value of the response value Y for the next time period.
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16
One of the ways to overcome the autocorrelation problem in a regression forecasting model is to transform the variables by taking the first-differences.
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17
One of the main techniques for isolating the effects of seasonality is decomposition.
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18
The long-term general direction of data is referred to as series.
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19
One of the main techniques for isolating the effects of seasonality is reconstitution.
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20
An exponential smoothing technique in which the smoothing constant alpha is equal to one is equivalent to a regression forecasting model.
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21
In exponential smoothing models,the value of the smoothing constant may be any number between ___________.

A)-1 and 1
B)-5 and 5
C)0 and 1
D)0 and 10
E)0 and 100
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22
A time series with forecast values and error terms is presented in the following table.The mean squared error (MSE)for this forecast is ___________. <strong>A time series with forecast values and error terms is presented in the following table.The mean squared error (MSE)for this forecast is ___________.  </strong> A)13.33 B)17.94 C)89.71 D)22.43 E)32.34

A)13.33
B)17.94
C)89.71
D)22.43
E)32.34
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23
Use of a smoothing constant value less than 0.5 in an exponential smoothing model gives more weight to ___________.

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
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24
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 error (ME)for this forecast is ___________. <strong>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 error (ME)for this forecast is ___________.  </strong> A)-0.50 B)0.50 C)1.50 D)7.00 E)3.00

A)-0.50
B)0.50
C)1.50
D)7.00
E)3.00
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25
A small value of the Durbin-Watson statistic indicates that successive error terms are positively correlated.
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26
Using a three-month moving average,the forecast value for November in the following time series is ____________. <strong>Using a three-month moving average,the forecast value for November in the following time series is ____________.  </strong> A)11.60 B)10.00 C)9.67 D)8.60 E)6.00

A)11.60
B)10.00
C)9.67
D)8.60
E)6.00
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27
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__________. <strong>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__________.  </strong> A)11.60 B)10.00 C)9.67 D)8.60 E)6.11

A)11.60
B)10.00
C)9.67
D)8.60
E)6.11
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28
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 ____________. <strong>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 ____________.  </strong> A)24 B)21 C)21.56 D)19.22 E)22

A)24
B)21
C)21.56
D)19.22
E)22
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29
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 ____________. <strong>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 ____________.  </strong> A)11.60 B)10.00 C)9.67 D)8.06 E)8.60

A)11.60
B)10.00
C)9.67
D)8.06
E)8.60
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30
Using a three-month moving average,the forecast value for October made at the end of September in the following time series would be ____________. <strong>Using a three-month moving average,the forecast value for October made at the end of September in the following time series would be ____________.  </strong> A)11.60 B)10.00 C)9.07 D)8.06 E)9.67

A)11.60
B)10.00
C)9.07
D)8.06
E)9.67
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31
Unweighted price indexes compare across the entire time period for which there is data.
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32
The city golf course is interested in starting a junior golf program.The golf pro 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 November in the following time series would be ____________. <strong>The city golf course is interested in starting a junior golf program.The golf pro 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 November in the following time series would be ____________.  </strong> A)24 B)21 C)21.56 D)19.22 E)22

A)24
B)21
C)21.56
D)19.22
E)22
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33
Use of a smoothing constant value greater than 0.5 in an exponential smoothing model gives more weight to ___________.

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
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34
When forecasting with exponential smoothing,data from previous periods is _________.

A)given equal importance
B)given exponentially increasing importance
C)ignored
D)given exponentially decreasing importance
E)linearly decreasing importance
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35
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 squared error (MSE)for this forecast is ___________. <strong>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 squared error (MSE)for this forecast is ___________.  </strong> A)-0.50 B)0.50 C)1.50 D)7.00 E)3.00

A)-0.50
B)0.50
C)1.50
D)7.00
E)3.00
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36
A time series with forecast values and error terms is presented in the following table.The mean absolute deviation (MAD)for this forecast is ___________. <strong>A time series with forecast values and error terms is presented in the following table.The mean absolute deviation (MAD)for this forecast is ___________.  </strong> A)3.54 B)7.41 C)4.43 D)17.72 E)4.34

A)3.54
B)7.41
C)4.43
D)17.72
E)4.34
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37
In statistics,the Winters' Three Parameter statistic is a test statistic used to detect the presence of autocorrelation in the residuals from a regression analysis.
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38
Autocorrelation in a regression forecasting model can be detected by the F test.
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39
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 ___________. <strong>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 ___________.  </strong> A)-0.50 B)0.50 C)1.50 D)7.00 E)3.00

A)-0.50
B)0.50
C)1.50
D)7.00
E)3.00
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40
A time series with forecast values and error terms is presented in the following table.The mean error (ME)for this forecast is ___________. <strong>A time series with forecast values and error terms is presented in the following table.The mean error (ME)for this forecast is ___________.  </strong> A)1.67 B)1.34 C)6.68 D)3.67 E)2.87

A)1.67
B)1.34
C)6.68
D)3.67
E)2.87
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41
Analysis of data for an autoregressive forecasting model produced the following tables. <strong>Analysis of data for an autoregressive forecasting model produced the following tables.     The results indicate that __________.</strong> 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 <strong>Analysis of data for an autoregressive forecasting model produced the following tables.     The results indicate that __________.</strong> 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 The results indicate that __________.

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
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42
The ratios of "actuals to moving averages" (seasonal indexes)for a time series are presented in the following table as percentages. <strong>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 __________.</strong> A)109.733 B)109.921 C)113.853 D)113.492 E)111.545 The final (completely adjusted)estimate of the seasonal index for Q1 is __________.

A)109.733
B)109.921
C)113.853
D)113.492
E)111.545
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43
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)trend and cyclical components
B)seasonal and irregular components
C)cyclical and irregular components
D)trend and seasonal components
E)irregular components
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44
Which of the following is not a component of time series data?

A)Trend
B)Seasonal fluctuations
C)Cyclical fluctuations
D)Normal fluctuations
E)Irregular fluctuations
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45
Analysis of data for an autoregressive forecasting model produced the following tables. <strong>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 predicted (forecast)value for August is __________.</strong> A)-101.00 B)104.54 C)218.71 D)21.56 E)-77.81 <strong>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 predicted (forecast)value for August is __________.</strong> A)-101.00 B)104.54 C)218.71 D)21.56 E)-77.81 The actual values of this time series,y,were 228,54,and 191 for May,June,and July,respectively.The predicted (forecast)value for August is __________.

A)-101.00
B)104.54
C)218.71
D)21.56
E)-77.81
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46
The city golf course is interested in starting a junior golf program.The golf pro 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 (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 __________. <strong>The city golf course is interested in starting a junior golf program.The golf pro 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 (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 __________.  </strong> A)24 B)21 C)21.56 D)19.22 E)22

A)24
B)21
C)21.56
D)19.22
E)22
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47
The following graph of a time-series data suggests a _______________ trend.

A)linear <strong>The following graph of a time-series data suggests a _______________ trend.</strong> A)linear   B)tangential C)cosine D)quadratic E)flat
B)tangential
C)cosine
D)quadratic
E)flat
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48
The following graph of time-series data suggests a _______________ trend. <strong>The following graph of time-series data suggests a _______________ trend.    </strong> A)linear B)quadratic C)cosine D)tangential E)flat <strong>The following graph of time-series data suggests a _______________ trend.    </strong> A)linear B)quadratic C)cosine D)tangential E)flat

A)linear
B)quadratic
C)cosine
D)tangential
E)flat
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49
Fitting a linear trend to 36 monthly data points (January 2011 = 1,February 2011 =2,March 2011 = 3,etc.)produced the following tables. <strong>Fitting a linear trend to 36 monthly data points (January 2011 = 1,February 2011 =2,March 2011 = 3,etc.)produced the following tables.     The projected trend value for January 2014 is ________.</strong> A)544.29 B)868.61 C)652.39 D)760.50 E)876.90 <strong>Fitting a linear trend to 36 monthly data points (January 2011 = 1,February 2011 =2,March 2011 = 3,etc.)produced the following tables.     The projected trend value for January 2014 is ________.</strong> A)544.29 B)868.61 C)652.39 D)760.50 E)876.90 The projected trend value for January 2014 is ________.

A)544.29
B)868.61
C)652.39
D)760.50
E)876.90
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50
In an autoregressive forecasting model,the independent variable(s)is (are)______.

A)time-lagged values of the dependent variable
B)first-order differences of the dependent variable
C)second-order,or higher,differences of the dependent variable
D)first-order quotients of the dependent variable
E)time-lagged values of the independent variable
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51
Analysis of data for an autoregressive forecasting model produced the following tables. <strong>Analysis of data for an autoregressive forecasting model produced the following tables.     The forecasting model is __________.</strong> 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 <strong>Analysis of data for an autoregressive forecasting model produced the following tables.     The forecasting model is __________.</strong> 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 The forecasting model is __________.

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
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52
Fitting a linear trend to 36 monthly data points (January 2011 = 1,February 2011 =2,March 2011 = 3,etc.)produced the following tables. <strong>Fitting a linear trend to 36 monthly data points (January 2011 = 1,February 2011 =2,March 2011 = 3,etc.)produced the following tables.     The projected trend value for January 2014 is ________.</strong> A)231.39 B)555.71 C)339.50 D)447.76 E)355.71 <strong>Fitting a linear trend to 36 monthly data points (January 2011 = 1,February 2011 =2,March 2011 = 3,etc.)produced the following tables.     The projected trend value for January 2014 is ________.</strong> A)231.39 B)555.71 C)339.50 D)447.76 E)355.71 The projected trend value for January 2014 is ________.

A)231.39
B)555.71
C)339.50
D)447.76
E)355.71
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53
The high and low values of the "ratios of actuals to moving average" are ignored when finalizing the seasonal index for a period (month or quarter)in time series decomposition.The rationale for this is to ________.

A)reduce the sample size
B)eliminate autocorrelation
C)minimize serial correlation
D)eliminate the irregular component
E)eliminate the trend
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54
The city golf course is interested in starting a junior golf program.The golf pro 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 (with weights of 5,3,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 would be ____________. <strong>The city golf course is interested in starting a junior golf program.The golf pro 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 (with weights of 5,3,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 would be ____________.  </strong> A)24 B)21 C)21.56 D)19.22 E)22

A)24
B)21
C)21.56
D)19.22
E)22
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55
What is the forecast for the Period 7 using a 3-period moving average technique,given the following time-series data for six past periods? <strong>What is the forecast for the Period 7 using a 3-period moving average technique,given the following time-series data for six past periods?  </strong> A)164.67 B)156.00 C)148.00 D)126.57 E)158.67

A)164.67
B)156.00
C)148.00
D)126.57
E)158.67
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56
The forecast value for August was 22 and the actual value turned out to be 19.Using exponential smoothing with α\alpha = 0.30,the forecast value for September would be ______.

A)21.1
B)19.9
C)18.1
D)22.9
E)21.0
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57
The following graph of a time-series data suggests a _______________ trend.

A)linear <strong>The following graph of a time-series data suggests a _______________ trend.</strong> A)linear   B)quadratic C)cosine D)tangential E)flat
B)quadratic
C)cosine
D)tangential
E)flat
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58
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.  <strong>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 _________.</strong> A)1.24 B)1.22 C)1.13 D)1.15 E)1.85   <strong>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 _________.</strong> A)1.24 B)1.22 C)1.13 D)1.15 E)1.85
Using α\alpha = 0.05 the critical value of the Durbin-Watson statistic,dL,is _________.

A)1.24
B)1.22
C)1.13
D)1.15
E)1.85
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59
Analysis of data for an autoregressive forecasting model produced the following tables. <strong>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 __________.</strong> A)-101.00 B)104.54 C)218.71 D)21.56 E)-77.81 <strong>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 __________.</strong> A)-101.00 B)104.54 C)218.71 D)21.56 E)-77.81 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 __________.

A)-101.00
B)104.54
C)218.71
D)21.56
E)-77.81
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60
The forecast value for September 21.1 and the actual value turned out to be 18.Using exponential smoothing with α\alpha = 0.30,the forecast value for October would be ______.

A)18.09
B)18.93
C)20.17
D)21.00
E)17.07
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61
A weighted aggregate price index where the weight for each item is computed by using the quantities of the base period is known as the a.Paasche Index
B.Simple Index
C.Laspeyres Index
D.Consumer Price index
E.Producer Price index
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62
The motivation for using an index number is to ________________.

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
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63
Index numbers facilitate comparison of ____________.

A)means
B)data over time
C)variances
D)samples
E)deviations
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64
Using 2000 as the base year,the 1990 value of the Paasche' Price Index is ______.(Quantities are averages for the student body.) <strong>Using 2000 as the base year,the 1990 value of the Paasche' Price Index is ______.(Quantities are averages for the student body.)  </strong> A)80.72 B)162.28 C)240.06 D)50.45 E)30.35

A)80.72
B)162.28
C)240.06
D)50.45
E)30.35
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65
Using 2011 as the base year,the 2010 value of the Paasche' Price Index is ______. <strong>Using 2011 as the base year,the 2010 value of the Paasche' Price Index is ______.  </strong> A)99.79 B)192.51 C)100.29 D)59.19 E)39.99

A)99.79
B)192.51
C)100.29
D)59.19
E)39.99
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66
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.  <strong>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 _________.</strong> A)1.54 B)1.42 C)1.43 D)1.44 E)1.85   <strong>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 _________.</strong> A)1.54 B)1.42 C)1.43 D)1.44 E)1.85
Using α\alpha = 0.05 the critical value of the Durbin-Watson statistic,dU,is _________.

A)1.54
B)1.42
C)1.43
D)1.44
E)1.85
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67
When constructing a weighted aggregate price index,the weights usually are _____.

A)prices of substitute items
B)prices of complementary items
C)quantities of the respective items
D)squared quantities of the respective items
E)quality of individual items
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68
Typically,the denominator used to calculate an index number is a measurement for the ____________ period.

A)base
B)current
C)spanning
D)intermediate
E)peak
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69
Weighted aggregate price indexes are also known as _______.

A)unbalanced indexes
B)balanced indexes
C)value indexes
D)multiplicative indexes
E)overall indexes
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70
Using 2011 as the base year,the 2010 value of the Laspeyres Price Index is ______. <strong>Using 2011 as the base year,the 2010 value of the Laspeyres Price Index is ______.  </strong> A)69.92 B)144.06 C)100.21 D)79.72 E)99.72

A)69.92
B)144.06
C)100.21
D)79.72
E)99.72
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71
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.  <strong>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.     Jim's calculated value for the Durbin-Watson statistic is 1.14.Using  \alpha = 0.05,the appropriate decision is: _________.</strong> A)do not reject H0:  \rho  = 0 B)reject H0:  \rho  = 0 C)do not reject H0:  \rho   \neq  0 D)the test is inconclusive E)reject H0:  \rho  ≠ 0   <strong>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.     Jim's calculated value for the Durbin-Watson statistic is 1.14.Using  \alpha = 0.05,the appropriate decision is: _________.</strong> A)do not reject H0:  \rho  = 0 B)reject H0:  \rho  = 0 C)do not reject H0:  \rho   \neq  0 D)the test is inconclusive E)reject H0:  \rho  ≠ 0
Jim's calculated value for the Durbin-Watson statistic is 1.14.Using α\alpha = 0.05,the appropriate decision is: _________.

A)do not reject H0: ρ\rho = 0
B)reject H0: ρ\rho = 0
C)do not reject H0: ρ\rho \neq 0
D)the test is inconclusive
E)reject H0: ρ\rho ≠ 0
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72
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.  <strong>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.     Jim's calculated value for the Durbin-Watson statistic is 1.93.Using  \alpha = 0.05,the appropriate decision is: _________.</strong> A)do not reject H0:  \rho  = 0 B)reject H0: \rho  ≠ 0 C)do not reject:  \rho   \neq  0 D)the test is inconclusive E)reject H0:  \rho  = 0   <strong>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.     Jim's calculated value for the Durbin-Watson statistic is 1.93.Using  \alpha = 0.05,the appropriate decision is: _________.</strong> A)do not reject H0:  \rho  = 0 B)reject H0: \rho  ≠ 0 C)do not reject:  \rho   \neq  0 D)the test is inconclusive E)reject H0:  \rho  = 0
Jim's calculated value for the Durbin-Watson statistic is 1.93.Using α\alpha = 0.05,the appropriate decision is: _________.

A)do not reject H0: ρ\rho = 0
B)reject H0: ρ\rho ≠ 0
C)do not reject: ρ\rho \neq 0
D)the test is inconclusive
E)reject H0: ρ\rho = 0
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73
A weighted aggregate price index where the weight for each item is computed by using the quantities of the year of interest is known as the a.Paasche Index
B.Simple Index
C.Laspeyres Index
D.Consumer Price index
E.Producer Price index
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74
Often,index numbers are expressed as ____________.

A)percentages
B)frequencies
C)cycles
D)regression coefficients
E)correlation coefficients
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75
Using 2010 as the base year,the 2012 value of a simple price index for the following price data is _____________. <strong>Using 2010 as the base year,the 2012 value of a simple price index for the following price data is _____________.  </strong> A)77.60 B)114.13 C)160.58 D)99.30 E)100.00

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