Question 1

The following graph of time-series data suggests a ___ trend.

Accepted Answer

A) quadratic 
B) cosine 
C) linear 
D) tangential 
E) flat 
A) quadratic 
B) cosine 
C) linear 
D) tangential 
E) flat C

Question 2

Autoregression is a multiple regression technique in which the independent variables are time-lagged versions of the dependent variable.

Accepted Answer

A) True 
 B)False  True

Question 3

The forecast value for September was 10.6 and the actual value turned out to be 7.Using exponential smoothing with $\alpha$ = 0.20,the forecast value for October would be ___.

Accepted Answer

A) 10.10 
B) 9.88 
C) 12.00 
D) 10.6 
E) 8.88 
A) 10.10 
B) 9.88 
C) 12.00 
D) 10.6 
E) 8.88 B

Question 4

The following graph of time-series data suggests a ___ trend.

Accepted Answer

A) linear 
B) quadratic 
C) cosine 
D) tangential 
E) flat 
A) linear 
B) quadratic 
C) cosine 
D) tangential 
E) flat

Question 5

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.

Accepted Answer

A) True 
 B)False

Question 6

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 
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 7

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

Accepted Answer

A) True 
 B)False

Question 8

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) 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

Question 9

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

Question 10

Using a three-month moving average,the forecast value for November in the following time series would be ___.

Accepted Answer

A) 7.67 
B) 8 
C) 9 
D) 6.89 
E) 11.00 
A) 7.67 
B) 8 
C) 9 
D) 6.89 
E) 11.00

Question 11

Describe smoothing techniques for forecasting models,including naive,simple average,moving average,weighted moving average,and exponential smoothing.

Accepted Answer

One group of time-series forecasting met

Question 12

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

Accepted Answer

A) 111.047 
B) 111.741 
C) 111.523 
D) 111.243 
E) 111.943 
A) 111.047 
B) 111.741 
C) 111.523 
D) 111.243 
E) 111.943

Question 13

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

Accepted Answer

A) True 
 B)False

Question 14

Autocorrelation in a regression forecasting model can be detected by the F test.

Accepted Answer

A) True 
 B)False

Question 15

Jim Royo,manager of Billings Building Supply (BBS),wants to develop a model to forecast BBS's monthly sales (in $1,000's).He selects the dollar value of residential building permits (in $10,000)as the predictor variable.An analysis of the data yielded the following tables:     
Jim's calculated value for the Durbin-Watson statistic is 1.93.Using $\alpha$ = 0.05,the appropriate decision is: ___.

Accepted Answer

A) do not reject H0: $\rho$ = 0 
B) reject H0:$\rho$≠ 00 
C) do not reject: $\rho$ $\neq$ 0 
D) the test is inconclusive 
E) reject H0: $\rho$ = 0 
A) do not reject H0: $\rho$ = 0 
B) reject H0:$\rho$≠ 00 
C) do not reject: $\rho$ $\neq$ 0 
D) the test is inconclusive 
E) reject H0: $\rho$ = 0

Question 16

Linear regression models cannot be used to analyze quadratic trends in time-series data.

Accepted Answer

A) True 
 B)False

Question 17

If autocorrelation occurs in regression analysis,then the confidence intervals and tests using the t and F distributions are no longer strictly applicable.

Accepted Answer

A) True 
 B)False

Question 18

When the error terms of a regression forecasting model are correlated the problem of multicollinearity occurs.

Accepted Answer

A) True 
 B)False

Question 19

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

Question 20

Often,index numbers are expressed as ___.

Accepted Answer

A) percentages 
B) frequencies 
C) cycles 
D) regression coefficients 
E) correlation coefficients 
A) percentages 
B) frequencies 
C) cycles 
D) regression coefficients 
E) correlation coefficients

The following graph of time-series data suggests a ___ trend.

Autoregression is a multiple regression technique in which the independent variables are time-lagged versions of the dependent variable.

The forecast value for September was 10.6 and the actual value turned out to be 7.Using exponential smoothing with $\alpha$ = 0.20,the forecast value for October would be ___.

The following graph of time-series data suggests a ___ trend.

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.

The motivation for using an index number is to ___.

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

Using a three-month moving average,the forecast value for October made at the end of September in the following time series would be ___.

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

Using a three-month moving average,the forecast value for November in the following time series would be ___.

Describe smoothing techniques for forecasting models,including naive,simple average,moving average,weighted moving average,and exponential smoothing.

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

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

Autocorrelation in a regression forecasting model can be detected by the F test.

Linear regression models cannot be used to analyze quadratic trends in time-series data.

If autocorrelation occurs in regression analysis,then the confidence intervals and tests using the t and F distributions are no longer strictly applicable.

When the error terms of a regression forecasting model are correlated the problem of multicollinearity occurs.

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 ___.

Often,index numbers are expressed as ___.

Introduction to Statistics

Charts and Graphs

Descriptive Statistics

Probability

Discrete Distributions

Continuous Distributions

Sampling and Sampling Distributions

Statistical Inference: Estimation for Single Populations

Statistical Inference: Hypothesis Testing for Single Populations

Statistical Inferences About Two Populations

Analysis of Variance and Design of Experiments

Simple Regression Analysis and Correlation

Multiple Regression Analysis

Building Multiple Regression Models

Analysis of Categorical Data

Nonparametric Statistics

Statistical Quality Control

Decision Analysis

Filters

Exam 15: Time-Series Forecasting and Index Numbers

The following graph of time-series data suggests a ___ trend.

Autoregression is a multiple regression technique in which the independent variables are time-lagged versions of the dependent variable.

The forecast value for September was 10.6 and the actual value turned out to be 7.Using exponential smoothing with α\alphaα = 0.20,the forecast value for October would be ___.

The following graph of time-series data suggests a ___ trend.

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.

The motivation for using an index number is to ___.

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

Using a three-month moving average,the forecast value for October made at the end of September in the following time series would be ___.

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

Using a three-month moving average,the forecast value for November in the following time series would be ___.

Describe smoothing techniques for forecasting models,including naive,simple average,moving average,weighted moving average,and exponential smoothing.

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

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

Autocorrelation in a regression forecasting model can be detected by the F test.

Linear regression models cannot be used to analyze quadratic trends in time-series data.

If autocorrelation occurs in regression analysis,then the confidence intervals and tests using the t and F distributions are no longer strictly applicable.

When the error terms of a regression forecasting model are correlated the problem of multicollinearity occurs.

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 ___.

Often,index numbers are expressed as ___.

Introduction to Statistics

Charts and Graphs

Descriptive Statistics

Probability

Discrete Distributions

Continuous Distributions

Sampling and Sampling Distributions

Statistical Inference: Estimation for Single Populations

Statistical Inference: Hypothesis Testing for Single Populations

Statistical Inferences About Two Populations

Analysis of Variance and Design of Experiments

Simple Regression Analysis and Correlation

Multiple Regression Analysis

Building Multiple Regression Models

Analysis of Categorical Data

Nonparametric Statistics

Statistical Quality Control

Decision Analysis

Filters

The forecast value for September was 10.6 and the actual value turned out to be 7.Using exponential smoothing with $\alpha$ = 0.20,the forecast value for October would be ___.

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