Question 1

Use the following price information for three grains.
   Calculate the Paasche index.

Accepted Answer

79.1
Paasc

Question 2

Seasonal variations are periodic patterns in a time series that must last at least one year.

Accepted Answer

A) True 
 B)False

Question 3

In a given week, the NYSE (New York Stock Exchange) is generally open from Monday through Friday. If we wanted to use the multiple regression method with dummy variables to study the impact of the day of the week on stock market performance, we would need ________ dummy variables.

Accepted Answer

A)  5 
B)  52 
C)  4 
D)  3 
E)  365 
A)  5 
B)  52 
C)  4 
D)  3 
E)  365

Question 4

In the multiplicative decomposition method, the centered moving averages provide an estimate of

Accepted Answer

A)  trend × seasonal. 
B)  trend × cycle. 
C)  seasonal × cycle. 
D)  trend × irregular. 
E)  seasonal × irregular. 
A)  trend × seasonal. 
B)  trend × cycle. 
C)  seasonal × cycle. 
D)  trend × irregular. 
E)  seasonal × irregular.

Question 5

Given the following data, compute the mean squared error (deviation).

Accepted Answer

MSD = 5275

Question 6

When a forecaster uses the ________ method, she or he assumes that the time series components are changing slowly over time.

Accepted Answer

A)  time series regression 
B)  exponential smoothing 
C)  index number 
D)  multiplicative decomposition 
A)  time series regression 
B)  exponential smoothing 
C)  index number 
D)  multiplicative decomposition

Question 7

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 8

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 9

XYZ Company, Annual Data   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 10

In the Durbin-Watson test, if the calculated d-statistic is greater than the upper value of the d-statistic, then

Accepted Answer

A)  we do not reject H0, which says the error terms are not autocorrelated. 
B)  we do reject H0, which says the error terms are not autocorrelated. 
C)  the test is inconclusive. 
D)  we do reject H0, which says the error terms are positively or negatively autocorrelated. 
A)  we do not reject H0, which says the error terms are not autocorrelated. 
B)  we do reject H0, which says the error terms are not autocorrelated. 
C)  the test is inconclusive. 
D)  we do reject H0, which says the error terms are positively or negatively autocorrelated.

Question 11

Consider a time series with 15 quarterly sales observations. Using the quadratic trend model, the following partial computer output was obtained.
   State the two-sided null and alternative hypotheses to test the significance of the t2 term.

Accepted Answer

Question 12

When deseasonalizing a time series observation, the actual time series observation is divided by its seasonal factor.

Accepted Answer

A) True 
 B)False

Question 13

Listed below are the prices of a pair of men's boots over a 50-year time period.
   Find the simple index numbers for the data with 1950 as the base year.

Accepted Answer

100.0, 144.0, 200, 310.7, 356.

Question 14

Consider the quarterly production data (in thousands of units) for the XYZ manufacturing company below. The normalized (adjusted) seasonal factors are winter = .9982, spring = .9263, summer = 1.139, and fall = .9365.
   Based on the following deseasonalized observations (dt), a trend line was estimated. The linear regression trend equation is trt = 10.1 + 1.91t.
Use the forecasting equation   t = tr1 × snt and calculate the forecasted demand for the fall quarter of 1998 and summer quarter of 2000.

Accepted Answer

fall 1998 = 16.595, summer 200

Question 15

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 16

If the errors produced by a forecasting method for 3 observations are +3, +3, and −3, then what is the mean absolute deviation?

Accepted Answer

A)  9 
B)  0 
C)  3 
D)  −3 
A)  9 
B)  0 
C)  3 
D)  −3

Question 17

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 18

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 Winters method 
A)  dummy variable regression 
B)  simple exponential smoothing 
C)  time series decomposition 
D)  multiplicative Winters method

Question 19

Consider the quarterly production data (in thousands of units) for the XYZ manufacturing company below.
   Calculate the ratio of actual production to the centered moving average values (snt × irt) for the entire time series.

Accepted Answer

1.00, .944, 1.037, .879, 1.25, .906, .93

Question 20

Consider the following data.
   Calculate S3 using simple exponential smoothing if S1 = 18.6 and α = .2.

Accepted Answer

S₃ = 19.06 S₂ = (.2)(2

Use the following price information for three grains. Calculate the Paasche index.

Seasonal variations are periodic patterns in a time series that must last at least one year.

In a given week, the NYSE (New York Stock Exchange) is generally open from Monday through Friday. If we wanted to use the multiple regression method with dummy variables to study the impact of the day of the week on stock market performance, we would need ________ dummy variables.

In the multiplicative decomposition method, the centered moving averages provide an estimate of

Given the following data, compute the mean squared error (deviation).

When a forecaster uses the ________ method, she or he assumes that the time series components are changing slowly over time.

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

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.

XYZ Company, Annual Data Based on the information given in the table above, what is the MSD?

In the Durbin-Watson test, if the calculated d-statistic is greater than the upper value of the d-statistic, then

Consider a time series with 15 quarterly sales observations. Using the quadratic trend model, the following partial computer output was obtained. State the two-sided null and alternative hypotheses to test the significance of the t² term.

When deseasonalizing a time series observation, the actual time series observation is divided by its seasonal factor.

Listed below are the prices of a pair of men's boots over a 50-year time period. Find the simple index numbers for the data with 1950 as the base year.

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

If the errors produced by a forecasting method for 3 observations are +3, +3, and −3, then what is the mean absolute deviation?

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

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

Consider the quarterly production data (in thousands of units) for the XYZ manufacturing company below. Calculate the ratio of actual production to the centered moving average values (sn_t × ir_t) for the entire time series.

Consider the following data. Calculate S₃ using simple exponential smoothing if S₁ = 18.6 and α = .2.

An Introduction to Business Statistics and Analytics

Descriptive Statistics and Analytics: Tabular and Graphical Methods

Descriptive Statistics and Analytics: Numerical Methods

Probability and Probability Models

Predictive Analytics I: Trees, K-Nearest Neighbors, Naive Bayes,

Discrete Random Variables

Continuous Random Variables

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 and Model Building

Predictive Analytics Ii: Logistic Regression, Discriminate Analysis,

Nonparametric Methods

Decision Theory

Filters

Exam 17: Time Series Forecasting and Index Numbers

Use the following price information for three grains. Calculate the Paasche index.

Seasonal variations are periodic patterns in a time series that must last at least one year.

In a given week, the NYSE (New York Stock Exchange) is generally open from Monday through Friday. If we wanted to use the multiple regression method with dummy variables to study the impact of the day of the week on stock market performance, we would need ________ dummy variables.

In the multiplicative decomposition method, the centered moving averages provide an estimate of

Given the following data, compute the mean squared error (deviation).

When a forecaster uses the ________ method, she or he assumes that the time series components are changing slowly over time.

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

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.

XYZ Company, Annual Data Based on the information given in the table above, what is the MSD?

In the Durbin-Watson test, if the calculated d-statistic is greater than the upper value of the d-statistic, then

Consider a time series with 15 quarterly sales observations. Using the quadratic trend model, the following partial computer output was obtained. State the two-sided null and alternative hypotheses to test the significance of the t2 term.

When deseasonalizing a time series observation, the actual time series observation is divided by its seasonal factor.

Listed below are the prices of a pair of men's boots over a 50-year time period. Find the simple index numbers for the data with 1950 as the base year.

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

If the errors produced by a forecasting method for 3 observations are +3, +3, and −3, then what is the mean absolute deviation?

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

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

Consider the quarterly production data (in thousands of units) for the XYZ manufacturing company below. Calculate the ratio of actual production to the centered moving average values (snt × irt) for the entire time series.

Consider the following data. Calculate S3 using simple exponential smoothing if S1 = 18.6 and α = .2.

An Introduction to Business Statistics and Analytics

Descriptive Statistics and Analytics: Tabular and Graphical Methods

Descriptive Statistics and Analytics: Numerical Methods

Probability and Probability Models

Predictive Analytics I: Trees, K-Nearest Neighbors, Naive Bayes,

Discrete Random Variables

Continuous Random Variables

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 and Model Building

Predictive Analytics Ii: Logistic Regression, Discriminate Analysis,

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.

Consider a time series with 15 quarterly sales observations. Using the quadratic trend model, the following partial computer output was obtained. State the two-sided null and alternative hypotheses to test the significance of the t² term.

Consider the quarterly production data (in thousands of units) for the XYZ manufacturing company below. Calculate the ratio of actual production to the centered moving average values (sn_t × ir_t) for the entire time series.

Consider the following data. Calculate S₃ using simple exponential smoothing if S₁ = 18.6 and α = .2.