Question 1

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

Accepted Answer

A) True 
 B)False

Question 2

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

Accepted Answer

A) 60 
B) -10 
C) 10 
D) 100 
A) 60 
B) -10 
C) 10 
D) 100

Question 3

When there is _______________ seasonal variation,the magnitude of the seasonal swing does not depend on the level of the time series.

Accepted Answer

A) cyclical 
B) constant 
C) irregular 
D) increasing 
A) cyclical 
B) constant 
C) irregular 
D) increasing

Question 4

The Laspeyres index and the Paasche index are both examples of _________ aggregate price indexes.

Accepted Answer

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

Question 5

A simple index is obtained by dividing the current value of a time series by the value of a time series in the _____ time period and by multiplying this ratio by 100.

Accepted Answer

A) base 
B) final 
C) current 
D) shortest 
A) base 
B) final 
C) current 
D) shortest

Question 6

Consider the following data:   
Calculate S5 using simple exponential smoothing if S3 = 19.064 and $\alpha$ = 0.2.

Accepted Answer

A) 19.48 
B) 19.85 
C) 18.80 
D) 19.80 
A) 19.48 
B) 19.85 
C) 18.80 
D) 19.80

Question 7

The following data on prices and quantities for the years 1995 and 2000 are given for three products.   Calculate the Laspeyres index.

Accepted Answer

The answer of The following data on prices and quantities...

Question 8

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.   What is the predicted value of y when t = 25?

Accepted Answer

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

Question 9

Use the following information for the three grains.   Calculate the Laspeyres index.

Accepted Answer

The answer of Use the following information for the three...

Question 10

The forecaster who uses MSD (mean squared deviations)to measure the effectiveness of forecasting methods would prefer method 1 that results in several smaller forecast errors to method 2 that results in one large forecast error equal to the sum of the absolute values of several small forecast errors given by method 1.

Accepted Answer

A) True 
 B)False

Question 11

When preparing a price index based on multiple products,if the price of each product is weighted by the quantity of the product purchased in a given period of time,the resulting index is called ___________ price index.

Accepted Answer

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

Question 12

Consider the following data and calculate S2 using simple exponential smoothing and $\alpha$ = 0.3.

Accepted Answer

A) 18.40 
B) 19.18 
C) 19.00 
D) 19.60 
A) 18.40 
B) 19.18 
C) 19.00 
D) 19.60

Question 13

Consider the quarterly production data (in thousands of units)for the XYZ manufacturing company below.   Calculate the 4 period (quarter)centered moving average for the entire time series.

Accepted Answer

16,18,20.2

Question 14

Dummy variables are used to model increasing seasonal variation.

Accepted Answer

A) True 
 B)False

Question 15

Since the ____________ index employs the base period quantities in all succeeding periods,it allows for ready comparisons for identical quantities of goods purchased between the base period and all succeeding periods.

Accepted Answer

A) Simple 
B) Aggregate 
C) Laspeyres 
D) Paasche 
E) Quantity 
A) Simple 
B) Aggregate 
C) Laspeyres 
D) Paasche 
E) Quantity

Question 16

Consider the following data:   
Use simple exponential smoothing with $\alpha$ = 0.2.and determine the forecast error for time period 1.

Accepted Answer

A) 1.6 
B) -1.6 
C) 0 
D) 2 
A) 1.6 
B) -1.6 
C) 0 
D) 2

Question 17

Given the following data   Compute the total error (sum of the error terms)

Accepted Answer

The answer of Given the following data   Compute...

Question 18

_______________ 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 19

Based on the information given in the table above,what is the average forecast error?

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 20

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.   Calculate the Mean Squared Deviation (MSD or MSE).

Accepted Answer

A) 18.355 
B) 3.671 
C) 13.494 
D) 6.314 
A) 18.355 
B) 3.671 
C) 13.494 
D) 6.314

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

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

When there is _______________ seasonal variation,the magnitude of the seasonal swing does not depend on the level of the time series.

The Laspeyres index and the Paasche index are both examples of _________ aggregate price indexes.

A simple index is obtained by dividing the current value of a time series by the value of a time series in the _____ time period and by multiplying this ratio by 100.

Consider the following data: $Consider the following data: Calculate S<sub>5</sub> using simple exponential smoothing if S<sub>3</sub> = 19.064 and \alpha = 0.2.$ Calculate S₅ using simple exponential smoothing if S₃ = 19.064 and $\alpha$ = 0.2.

The following data on prices and quantities for the years 1995 and 2000 are given for three products. Calculate the Laspeyres index.

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. What is the predicted value of y when t = 25?

Use the following information for the three grains. Calculate the Laspeyres index.

When preparing a price index based on multiple products,if the price of each product is weighted by the quantity of the product purchased in a given period of time,the resulting index is called ___________ price index.

Consider the following data and calculate S₂ using simple exponential smoothing and $\alpha$ = 0.3. $Consider the following data and calculate S<sub>2</sub> using simple exponential smoothing and \alpha = 0.3.$

Consider the quarterly production data (in thousands of units)for the XYZ manufacturing company below. Calculate the 4 period (quarter)centered moving average for the entire time series.

Dummy variables are used to model increasing seasonal variation.

Since the ____________ index employs the base period quantities in all succeeding periods,it allows for ready comparisons for identical quantities of goods purchased between the base period and all succeeding periods.

Consider the following data: $Consider the following data: Use simple exponential smoothing with \alpha = 0.2.and determine the forecast error for time period 1.$ Use simple exponential smoothing with $\alpha$ = 0.2.and determine the forecast error for time period 1.

Given the following data Compute the total error (sum of the error terms)

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

Based on the information given in the table above,what is the average forecast error?

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. Calculate the Mean Squared Deviation (MSD or MSE).

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

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

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

When there is _______________ seasonal variation,the magnitude of the seasonal swing does not depend on the level of the time series.

The Laspeyres index and the Paasche index are both examples of _________ aggregate price indexes.

A simple index is obtained by dividing the current value of a time series by the value of a time series in the _____ time period and by multiplying this ratio by 100.

Consider the following data: Calculate S5 using simple exponential smoothing if S3 = 19.064 and α\alphaα = 0.2.

The following data on prices and quantities for the years 1995 and 2000 are given for three products. Calculate the Laspeyres index.

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. What is the predicted value of y when t = 25?

Use the following information for the three grains. Calculate the Laspeyres index.

When preparing a price index based on multiple products,if the price of each product is weighted by the quantity of the product purchased in a given period of time,the resulting index is called ___________ price index.

Consider the following data and calculate S2 using simple exponential smoothing and α\alphaα = 0.3.

Consider the quarterly production data (in thousands of units)for the XYZ manufacturing company below. Calculate the 4 period (quarter)centered moving average for the entire time series.

Dummy variables are used to model increasing seasonal variation.

Since the ____________ index employs the base period quantities in all succeeding periods,it allows for ready comparisons for identical quantities of goods purchased between the base period and all succeeding periods.

Consider the following data: Use simple exponential smoothing with α\alphaα = 0.2.and determine the forecast error for time period 1.

Given the following data Compute the total error (sum of the error terms)

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

Based on the information given in the table above,what is the average forecast error?

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. Calculate the Mean Squared Deviation (MSD or MSE).

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

Consider the following data: $Consider the following data: Calculate S<sub>5</sub> using simple exponential smoothing if S<sub>3</sub> = 19.064 and \alpha = 0.2.$ Calculate S₅ using simple exponential smoothing if S₃ = 19.064 and $\alpha$ = 0.2.

Consider the following data and calculate S₂ using simple exponential smoothing and $\alpha$ = 0.3. $Consider the following data and calculate S<sub>2</sub> using simple exponential smoothing and \alpha = 0.3.$

Consider the following data: $Consider the following data: Use simple exponential smoothing with \alpha = 0.2.and determine the forecast error for time period 1.$ Use simple exponential smoothing with $\alpha$ = 0.2.and determine the forecast error for time period 1.

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. Calculate the Mean Squared Deviation (MSD or MSE).