Question 1

The recurring up-and-down movement of a time series around trend levels that last more than one calendar year is called ____________.

Accepted Answer

A)  constant variation 
B)  cyclical variation 
C)  seasonal variation 
D)  irregular variation 
A)  constant variation 
B)  cyclical variation 
C)  seasonal variation 
D)  irregular variation

Question 2

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 3

Given the following data,compute the total error (sum of the error terms).

Accepted Answer

Total erro

Question 4

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 MSD.

Accepted Answer

A)  MSD = 6 
B)  MSD = 3.3333 
C)  MSD = 7.0 
D)  MSD = 2 
E)  MSD = 2.4 
A)  MSD = 6 
B)  MSD = 3.3333 
C)  MSD = 7.0 
D)  MSD = 2 
E)  MSD = 2.4

Question 5

Box-Jenkins methodology is a more sophisticated approach to forecasting a time series with components that might be changing over time.

Accepted Answer

A) True 
 B)False

Question 6

Forecasters using a multiplicative decomposition model or time series regression model,assume that the time series components are changing over time.

Accepted Answer

A) True 
 B)False

Question 7

A time series decomposition method would not be used to forecast seasonal data.

Accepted Answer

A) True 
 B)False

Question 8

Causal variables can be used in forecasting models.

Accepted Answer

A) True 
 B)False

Question 9

Consider a time series with 15 quarterly sales observations.Using the quadratic trend model,the following partial computer output was obtained.   Test the significance of the t2 term at α =.05.State the critical T value (rejection point)and the p-value.Make your decision using a two-sided null hypothesis.

Accepted Answer

T = −3.80,p-value = .001,reject H₀. H₀: β_t²

Question 10

The Durbin-Watson statistic is used to detect _____________.

Accepted Answer

A)  first-order autocorrelation 
B)  exponential smoothing 
C)  multiplicative decomposing 
D)  irregular variation 
A)  first-order autocorrelation 
B)  exponential smoothing 
C)  multiplicative decomposing 
D)  irregular variation

Question 11

Exponential smoothing is a forecasting method that applies equal weights to the time series observations.

Accepted Answer

A) True 
 B)False

Question 12

Given the following data,compute the total error (sum of the error terms).

Accepted Answer

The answer of Given the following data,compute the total error...

Question 13

In general,the number of dummy variables used to model constant seasonal variation is equal to the number of

Accepted Answer

A)  seasons. 
B)  seasons minus 1. 
C)  seasons plus 1. 
D)  seasons minus 2. 
E)  seasons divided by two. 
A)  seasons. 
B)  seasons minus 1. 
C)  seasons plus 1. 
D)  seasons minus 2. 
E)  seasons divided by two.

Question 14

Dummy variables are used to model increasing seasonal variation.

Accepted Answer

A) True 
 B)False

Question 15

Consider the following set of quarterly sales data,given in thousands of dollars.   The following dummy variable model that incorporates a linear trend and constant seasonal variation was used: y(t)= B0 + B1t + BQ1(Q1)+ BQ2(Q2)+ BQ3(Q3)+ Et.In this model,there are 3 binary seasonal variables (Q1,Q2,and Q3),where Qi is a binary (0,1)variable defined as:
Qi = 1,if the time series data is associated with quarter i;
Qi = 0,if the time series data is not associated with quarter i.The results associated with this data and model are given in the following Minitab computer output.The regression equation is
Sales = 2442 + 6.2 Time − 693 Q1 − 1499 Q2 + 153 Q3   Provide a managerial interpretation of the regression coefficient for the variable "time."

Accepted Answer

It is estimated that

Question 16

A univariate time-series model is used to predict future values of a time series based only upon past values of a time series.

Accepted Answer

A) True 
 B)False

Question 17

When deseasonalizing a time series observation,we divide the actual time series observation by its ___________.

Accepted Answer

A)  irregular factor 
B)  cyclical factor 
C)  seasonal factor 
D)  weighted aggregate factor 
A)  irregular factor 
B)  cyclical factor 
C)  seasonal factor 
D)  weighted aggregate factor

Question 18

A positive autocorrelation implies that negative error terms will be followed by negative error terms.

Accepted Answer

A) True 
 B)False

Question 19

A simple exponential forecasting method would not be used to forecast seasonal data.

Accepted Answer

A) True 
 B)False

Question 20

Cyclical variation exists when the magnitude of the seasonal swing does not depend on the level of a time series.

Accepted Answer

A) True 
 B)False

The recurring up-and-down movement of a time series around trend levels that last more than one calendar year is called ____________.

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

Given the following data,compute the total error (sum of the error terms).

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 MSD.

Box-Jenkins methodology is a more sophisticated approach to forecasting a time series with components that might be changing over time.

Forecasters using a multiplicative decomposition model or time series regression model,assume that the time series components are changing over time.

A time series decomposition method would not be used to forecast seasonal data.

Causal variables can be used in forecasting models.

The Durbin-Watson statistic is used to detect _____________.

Exponential smoothing is a forecasting method that applies equal weights to the time series observations.

Given the following data,compute the total error (sum of the error terms).

In general,the number of dummy variables used to model constant seasonal variation is equal to the number of

Dummy variables are used to model increasing seasonal variation.

A univariate time-series model is used to predict future values of a time series based only upon past values of a time series.

When deseasonalizing a time series observation,we divide the actual time series observation by its ___________.

A positive autocorrelation implies that negative error terms will be followed by negative error terms.

A simple exponential forecasting method would not be used to forecast seasonal data.

Cyclical variation exists when the magnitude of the seasonal swing does not depend on the level of a time series.

An Introduction to Business Statistics

Descriptive Statistics: Tabular and Graphical Methods

Descriptive Statistics: Numerical Methods

Probability

Discrete Random Variables

Continuous Random Variables

Sampling and Sampling Distributions

Confidence Intervals

Hypothesis Testing

Statistical Inferences for Means and Proportions

Statistical Inferences for Population Variances

Experimental Design and Analysis of Variance

Chi-Square Tests

Simple Linear Regression Analysis

Time Series Forecasting and Index Numbers

Nonparametric Methods

Decision Theory

Filters

Exam 15: Multiple Regression and Model Building

The recurring up-and-down movement of a time series around trend levels that last more than one calendar year is called ____________.

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

Given the following data,compute the total error (sum of the error terms).

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 MSD.

Box-Jenkins methodology is a more sophisticated approach to forecasting a time series with components that might be changing over time.

Forecasters using a multiplicative decomposition model or time series regression model,assume that the time series components are changing over time.

A time series decomposition method would not be used to forecast seasonal data.

Causal variables can be used in forecasting models.

The Durbin-Watson statistic is used to detect _____________.

Exponential smoothing is a forecasting method that applies equal weights to the time series observations.

Given the following data,compute the total error (sum of the error terms).

In general,the number of dummy variables used to model constant seasonal variation is equal to the number of

Dummy variables are used to model increasing seasonal variation.

A univariate time-series model is used to predict future values of a time series based only upon past values of a time series.

When deseasonalizing a time series observation,we divide the actual time series observation by its ___________.

A positive autocorrelation implies that negative error terms will be followed by negative error terms.

A simple exponential forecasting method would not be used to forecast seasonal data.

Cyclical variation exists when the magnitude of the seasonal swing does not depend on the level of a time series.

An Introduction to Business Statistics

Descriptive Statistics: Tabular and Graphical Methods

Descriptive Statistics: Numerical Methods

Probability

Discrete Random Variables

Continuous Random Variables

Sampling and Sampling Distributions

Confidence Intervals

Hypothesis Testing

Statistical Inferences for Means and Proportions

Statistical Inferences for Population Variances

Experimental Design and Analysis of Variance

Chi-Square Tests

Simple Linear Regression Analysis

Time Series Forecasting and Index Numbers

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 MSD.