Question 1

Consider a time series with 15 quarterly sales observations.Using the quadratic trend model,the following partial computer output was obtained.

Accepted Answer

\[\begin{array} { l l l l } 
\text { Var

Question 2

When there is first-order autocorrelation,the error term in period t is related to the error term in period ______.

Accepted Answer

A) t 
B) t + 1 
C) t - 1 
D) t - 2 
A) t 
B) t + 1 
C) t - 1 
D) t - 2

Question 3

Use the following price information for three grains.

Accepted Answer

\[\begin{array} { l c c c c } 
& \text {

Question 4

The Consumer Price Index and the Producer Price Index are both calculated using the ___________ index formula.

Accepted Answer

A) Paasche 
B) Weighted aggregate 
C) Laspeyres 
D) Cyclical (seasonal) 
A) Paasche 
B) Weighted aggregate 
C) Laspeyres 
D) Cyclical (seasonal)

Question 5

A _______________ index is most useful if the base quantities provide a reasonable representation of consumption patterns in succeeding time periods.

Accepted Answer

A) Paasche 
B) Weighted aggregate 
C) Laspeyres 
D) Cyclical (seasonal) 
A) Paasche 
B) Weighted aggregate 
C) Laspeyres 
D) Cyclical (seasonal)

Question 6

Consider the following set of quarterly sales data,given in thousands of dollars.

Accepted Answer

\[\begin{array} { l r r r } 
\text { Qua

Question 7

The ___________ test is a test for first-order positive autocorrelation.

Accepted Answer

A) Durbin-Watson 
B) MSD 
C) MAD 
D) Multiplicative Winters 
A) Durbin-Watson 
B) MSD 
C) MAD 
D) Multiplicative Winters

Question 8

Box-Jenkins models describe the future time series value by using a nonseasonal autoregressive term when the SAC dies down fairly quickly (at lags 12 and 24)and the SPAC has a spike at lag 12 and cuts off after lag 12.

Accepted Answer

A) True 
 B)False

Question 9

The linear regression trend model was applied to a time series of sales data based on the last 16 months of sales.The following partial computer output was obtained:

Accepted Answer

\[\begin{array} { l l l l } 
& \text { V

Question 10

Trend refers to a long-run upward or downward movement of a time series over a period of time.

Accepted Answer

A) True 
 B)False

Question 11

Consider the following set of quarterly sales data given in thousands of dollars.

Accepted Answer

\[\begin{array} { l r r r } 
\text { Qua

Question 12

Listed below are the prices of a pair of men's boots over a 50-year time period.

Accepted Answer

\[\begin{array} { | l | l | } 
\hline \t

Question 13

A forecasting method that weights recent observations more heavily is called _____________.

Accepted Answer

A) Time series analysis 
B) First-order autocorrelation 
C) Multiplicative decomposition 
D) Exponential smoothing 
A) Time series analysis 
B) First-order autocorrelation 
C) Multiplicative decomposition 
D) Exponential smoothing

Question 14

The no-trend time series model is given by:

Accepted Answer

A) TRt = B0 + B1t. 
B) TRt = B0. 
C) TRt = B0 + B1t + B2t2. 
D) TRt = B0 + Bln(t). 
A) TRt = B0 + B1t. 
B) TRt = B0. 
C) TRt = B0 + B1t + B2t2. 
D) TRt = B0 + Bln(t).

Question 15

When using moving averages to estimate the seasonal factors,we need to compute the centered moving average if there are an odd number of seasons.

Accepted Answer

A) True 
 B)False

Question 16

The demand for a product for the last six years has been 15,15,17,18,20,and 19.The manager wants to predict the demand for this time series using the following simple linear trend equation: trt = 12 + 2t.Use this equation to forecast the demand for this product,and then calculate the MAD.

Accepted Answer

A) MAD = 1.333 
B) MAD = 1.6 
C) MAD = 2.0 
D) MAD = 2.333 
E) MAD = 2.5 
A) MAD = 1.333 
B) MAD = 1.6 
C) MAD = 2.0 
D) MAD = 2.333 
E) MAD = 2.5

Question 17

Box-Jenkins methodology begins by determining if the time series under consideration is stationary.

Accepted Answer

A) True 
 B)False

Question 18

Based on the following data,a forecaster used simple exponential smoothing and determined the following: S0 = 19,S1 = 18.6,S2 = 19.08,S3 = 19.064,S4 = 19.851,and S5 = 19.481.

Accepted Answer

\[\begin{array} { c c } 
\text { Time }

Question 19

Consider the following set of quarterly sales data,given in thousands of dollars.

Accepted Answer

\[\begin{array} { l r r r } 
\text { Qua

Question 20

Consider the following set of quarterly sales data,given in thousands of dollars.

Accepted Answer

\[\begin{array} { l r r r } 
\text { Qua

Consider a time series with 15 quarterly sales observations.Using the quadratic trend model,the following partial computer output was obtained.

When there is first-order autocorrelation,the error term in period t is related to the error term in period ______.

Use the following price information for three grains.

The Consumer Price Index and the Producer Price Index are both calculated using the ___________ index formula.

A _______________ index is most useful if the base quantities provide a reasonable representation of consumption patterns in succeeding time periods.

Consider the following set of quarterly sales data,given in thousands of dollars.

The ___________ test is a test for first-order positive autocorrelation.

Box-Jenkins models describe the future time series value by using a nonseasonal autoregressive term when the SAC dies down fairly quickly (at lags 12 and 24)and the SPAC has a spike at lag 12 and cuts off after lag 12.

The linear regression trend model was applied to a time series of sales data based on the last 16 months of sales.The following partial computer output was obtained:

Trend refers to a long-run upward or downward movement of a time series over a period of time.

Consider the following set of quarterly sales data given in thousands of dollars.

Listed below are the prices of a pair of men's boots over a 50-year time period.

A forecasting method that weights recent observations more heavily is called _____________.

The no-trend time series model is given by:

When using moving averages to estimate the seasonal factors,we need to compute the centered moving average if there are an odd number of seasons.

The demand for a product for the last six years has been 15,15,17,18,20,and 19.The manager wants to predict the demand for this time series using the following simple linear trend equation: tr_t = 12 + 2t.Use this equation to forecast the demand for this product,and then calculate the MAD.

Box-Jenkins methodology begins by determining if the time series under consideration is stationary.

Based on the following data,a forecaster used simple exponential smoothing and determined the following: S₀ = 19,S₁ = 18.6,S₂ = 19.08,S₃ = 19.064,S₄ = 19.851,and S₅ = 19.481.

Consider the following set of quarterly sales data,given in thousands of dollars.

Consider the following set of quarterly sales data,given in thousands of dollars.

Statistical Inferences for Population Variances

Experimental Design and Analysis of Variance

Chi-Square Tests

Simple Linear Regression Analysis

Multiple Regression and Model Building

Process Improvement Using Control Charts

Nonparametric Methods

Decision Theory

Filters

Exam 16: Time Series Forecasting and Index Numbers

Consider a time series with 15 quarterly sales observations.Using the quadratic trend model,the following partial computer output was obtained.

When there is first-order autocorrelation,the error term in period t is related to the error term in period ______.

Use the following price information for three grains.

The Consumer Price Index and the Producer Price Index are both calculated using the ___________ index formula.

A _______________ index is most useful if the base quantities provide a reasonable representation of consumption patterns in succeeding time periods.

Consider the following set of quarterly sales data,given in thousands of dollars.

The ___________ test is a test for first-order positive autocorrelation.

Box-Jenkins models describe the future time series value by using a nonseasonal autoregressive term when the SAC dies down fairly quickly (at lags 12 and 24)and the SPAC has a spike at lag 12 and cuts off after lag 12.

The linear regression trend model was applied to a time series of sales data based on the last 16 months of sales.The following partial computer output was obtained:

Trend refers to a long-run upward or downward movement of a time series over a period of time.

Consider the following set of quarterly sales data given in thousands of dollars.

Listed below are the prices of a pair of men's boots over a 50-year time period.

A forecasting method that weights recent observations more heavily is called _____________.

The no-trend time series model is given by:

When using moving averages to estimate the seasonal factors,we need to compute the centered moving average if there are an odd number of seasons.

The demand for a product for the last six years has been 15,15,17,18,20,and 19.The manager wants to predict the demand for this time series using the following simple linear trend equation: trt = 12 + 2t.Use this equation to forecast the demand for this product,and then calculate the MAD.

Box-Jenkins methodology begins by determining if the time series under consideration is stationary.

Based on the following data,a forecaster used simple exponential smoothing and determined the following: S0 = 19,S1 = 18.6,S2 = 19.08,S3 = 19.064,S4 = 19.851,and S5 = 19.481.

Consider the following set of quarterly sales data,given in thousands of dollars.

Consider the following set of quarterly sales data,given in thousands of dollars.

Statistical Inferences for Population Variances

Experimental Design and Analysis of Variance

Chi-Square Tests

Simple Linear Regression Analysis

Multiple Regression and Model Building

Process Improvement Using Control Charts

Nonparametric Methods

Decision Theory

Filters

The demand for a product for the last six years has been 15,15,17,18,20,and 19.The manager wants to predict the demand for this time series using the following simple linear trend equation: tr_t = 12 + 2t.Use this equation to forecast the demand for this product,and then calculate the MAD.

Based on the following data,a forecaster used simple exponential smoothing and determined the following: S₀ = 19,S₁ = 18.6,S₂ = 19.08,S₃ = 19.064,S₄ = 19.851,and S₅ = 19.481.