Question 1

When using simple exponential smoothing,the more recent the time series observation,the _________ its corresponding weight.

Accepted Answer

A) larger 
B) smaller 
C) irregular 
D) cyclical 
A) larger 
B) smaller 
C) irregular 
D) cyclical

Question 2

A restaurant has been experiencing higher sales during the weekends of compared to the weekdays.Daily restaurant sales patterns for this restaurant over a week are an example of _________ component of time series.

Accepted Answer

A) Trend 
B) Seasonal 
C) Cyclical 
D) Irregular 
A) Trend 
B) Seasonal 
C) Cyclical 
D) Irregular

Question 3

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

Accepted Answer

A) True 
 B)False

Question 4

Based on the information given in the table above,what is the MSD?

Accepted Answer

A) 1.3333 
B) 1.6667 
C) 2.5 
D) 3.3333 
E) 4.5 
A) 1.3333 
B) 1.6667 
C) 2.5 
D) 3.3333 
E) 4.5

Question 5

The linear regression trend model was applied to a time series sales data based on the last 24 months' sales.The following partial computer output was obtained.   
Test the significance of the time term at $\alpha$ = .05.State the critical t value and make your decision using a two-sided alternative.

Accepted Answer

t = 8.65,reject H₀

Question 6

The price and quantity of several food items are listed below for the years 1990 and 2000.   Compute the Laspeyres index using 1990 as the base year.

Accepted Answer

The answer of The price and quantity of several food...

Question 7

Consider the quarterly production data (in thousands of units)for the XYZ manufacturing company below.The normalized (adjusted)seasonal factors are .9982,.9263,1.139,.9365 for winter,spring,summer and fall respectively.   Based on the following deseasonalized observations (dt)given below,a trend line was estimated.   The following MINITAB output gives the straight-line trend equation fitted to the deseasonalized observations.Based on the trend equation given below,calculate the trend value for each period in the time series.
The regression equation is
Deseasonalized = 10.1 + 1.91 Time

Accepted Answer

12.01,13.91,15.82,17.72,19.63,

Question 8

Based on the information given in the table above,what is the MAD?

Accepted Answer

A) 1.3333 
B) 1.6667 
C) 2.5 
D) 3.3333 
E) 4.5 
A) 1.3333 
B) 1.6667 
C) 2.5 
D) 3.3333 
E) 4.5

Question 9

The upward or downward movement that characterizes a time series over a period of time is referred to as ____.

Accepted Answer

A) seasonal 
B) cyclical 
C) trend 
D) irregular 
A) seasonal 
B) cyclical 
C) trend 
D) irregular

Question 10

Consider the quarterly production data (in thousands of units)for the XYZ manufacturing company below.The normalized (adjusted)seasonal factors are .9982,.9263,1.139,.9365 for winter,spring,summer and fall respectively.   Based on the following deseasonalized observations (dt)given below,a trend line was estimated.The linear regression trend equation is: trt = 10.1 + 1.91 (t).Use the forecasting equation   and calculate the forecasted demand for the fall quarter of 1998 and summer quarter of 2000.

Accepted Answer

Question 11

If a time series exhibits increasing seasonal variation,one approach is to first use a ______________ transformation that produces a transformed time series that exhibits constant seasonal variation.Then,_________ variables can be used to model the time series with constant seasonal variation.

Accepted Answer

A) autocorrelation,dummy 
B) fractional power,dummy 
C) fractional power,constant 
D) autocorrelation,constant 
A) autocorrelation,dummy 
B) fractional power,dummy 
C) fractional power,constant 
D) autocorrelation,constant

Question 12

In the multiplicative decomposition method,the centered moving averages provide an estimate of trend x _____.

Accepted Answer

A) index 
B) cycle 
C) seasonal 
D) irregular 
A) index 
B) cycle 
C) seasonal 
D) irregular

Question 13

The linear regression trend model was applied to a time series sales data based on the last 24 months' sales.The following partial computer output was obtained.   Write the prediction equation.

Accepted Answer

The answer of The linear regression trend model was applied...

Question 14

Two forecasting models were used to predict the future values of a time series.The forecasts are shown below with the actual values:   Calculate the mean squared deviation (MSD)for Model 1.

Accepted Answer

The answer of Two forecasting models were used to predict...

Question 15

Which of the following time series forecasting methods would not be used to forecast seasonal data?

Accepted Answer

A) Dummy variable regression 
B) Simple exponential smoothing 
C) Time series decomposition 
D) Multiplicative Winter's method 
A) Dummy variable regression 
B) Simple exponential smoothing 
C) Time series decomposition 
D) Multiplicative Winter's method

Question 16

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:   Write the prediction equation.

Accepted Answer

y = 18.100

Question 17

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 18

When a forecaster uses the _________________ method she or he assumes that the time series components are changing quickly over time.

Accepted Answer

A) Time series regression 
B) Simple exponential smoothing 
C) Box and Jenkins 
D) Multiplicative decomposition 
A) Time series regression 
B) Simple exponential smoothing 
C) Box and Jenkins 
D) Multiplicative decomposition

Question 19

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.What are the forecast errors for the 5th and 6th years?

Accepted Answer

A) 0,-3 
B) 0,+ 3 
C) + 2,+ 5 
D) -2,-5 
E) -1,-4 
A) 0,-3 
B) 0,+ 3 
C) + 2,+ 5 
D) -2,-5 
E) -1,-4

Question 20

Consider the quarterly production data (in thousands of units)for the XYZ manufacturing company below.The normalized (adjusted)seasonal factors are .9982,.9263,1.139,.9365 for winter,spring,summer,and fall respectively.Calculate the deseasonalized production value for each observation in the time series.

Accepted Answer

9.02,17.27,14.05,18.

When using simple exponential smoothing,the more recent the time series observation,the _________ its corresponding weight.

A restaurant has been experiencing higher sales during the weekends of compared to the weekdays.Daily restaurant sales patterns for this restaurant over a week are an example of _________ component of time series.

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

Based on the information given in the table above,what is the MSD?

The price and quantity of several food items are listed below for the years 1990 and 2000. Compute the Laspeyres index using 1990 as the base year.

Based on the information given in the table above,what is the MAD?

The upward or downward movement that characterizes a time series over a period of time is referred to as ____.

If a time series exhibits increasing seasonal variation,one approach is to first use a ______ transformation that produces a transformed time series that exhibits constant seasonal variation.Then,_ variables can be used to model the time series with constant seasonal variation.

In the multiplicative decomposition method,the centered moving averages provide an estimate of trend x _____.

The linear regression trend model was applied to a time series sales data based on the last 24 months' sales.The following partial computer output was obtained. Write the prediction equation.

Two forecasting models were used to predict the future values of a time series.The forecasts are shown below with the actual values: Calculate the mean squared deviation (MSD)for Model 1.

Which of the following time series forecasting methods would not be used to forecast seasonal data?

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: Write the prediction equation.

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

When a forecaster uses the _________________ method she or he assumes that the time series components are changing quickly over time.

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.What are the forecast errors for the 5^th and 6^th years?

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 Based on Two Samples

Experimental Design and Analysis of Variance

Chi-Square Tests

Simple Linear Regression Analysis

Multiple Regression

Model Building and Model Diagnostics

Process Improvement Using Control Charts

Nonparametric Methods

Decision Theory

Filters

Exam 16: Time Series Forecasting

When using simple exponential smoothing,the more recent the time series observation,the _________ its corresponding weight.

A restaurant has been experiencing higher sales during the weekends of compared to the weekdays.Daily restaurant sales patterns for this restaurant over a week are an example of _________ component of time series.

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

Based on the information given in the table above,what is the MSD?

The price and quantity of several food items are listed below for the years 1990 and 2000. Compute the Laspeyres index using 1990 as the base year.

Based on the information given in the table above,what is the MAD?

The upward or downward movement that characterizes a time series over a period of time is referred to as ____.

If a time series exhibits increasing seasonal variation,one approach is to first use a ______________ transformation that produces a transformed time series that exhibits constant seasonal variation.Then,_________ variables can be used to model the time series with constant seasonal variation.

In the multiplicative decomposition method,the centered moving averages provide an estimate of trend x _____.

The linear regression trend model was applied to a time series sales data based on the last 24 months' sales.The following partial computer output was obtained. Write the prediction equation.

Two forecasting models were used to predict the future values of a time series.The forecasts are shown below with the actual values: Calculate the mean squared deviation (MSD)for Model 1.

Which of the following time series forecasting methods would not be used to forecast seasonal data?

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: Write the prediction equation.

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

When a forecaster uses the _________________ method she or he assumes that the time series components are changing quickly over time.

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.What are the forecast errors for the 5th and 6th years?

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 Based on Two Samples

Experimental Design and Analysis of Variance

Chi-Square Tests

Simple Linear Regression Analysis

Multiple Regression

Model Building and Model Diagnostics

Process Improvement Using Control Charts

Nonparametric Methods

Decision Theory

Filters

If a time series exhibits increasing seasonal variation,one approach is to first use a ______ transformation that produces a transformed time series that exhibits constant seasonal variation.Then,_ variables can be used to model the time series with constant seasonal variation.

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.What are the forecast errors for the 5^th and 6^th years?