Question 1

Weighting in exponential smoothing is accomplished by using _____________.

Accepted Answer

A)  first-order autocorrelation 
B)  smoothing constants 
C)  the Durbin-Watson method 
D)  multiplicative decomposing 
A)  first-order autocorrelation 
B)  smoothing constants 
C)  the Durbin-Watson method 
D)  multiplicative decomposing B

Question 2

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 average forecast error.

Accepted Answer

.3848 Average forecast error = ∑e_i/# time periods = [(−1.6)+ (1.92)+ (−.064)+ (3.149)+ (−1.481)]/5 = 1.924/5 = .3848

Question 3

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 MAD.

Accepted Answer

A)  MAD = 1.333 
B)  MAD = 1.6 
C)  MAD = 2.0 
D)  MAD = 2.333 
E)  MAD = 2.5 
A)  MAD = 1.333 
B)  MAD = 1.6 
C)  MAD = 2.0 
D)  MAD = 2.333 
E)  MAD = 2.5 C

Question 4

Consider the following data.   Calculate S3 using simple exponential smoothing if S1 = 18.6 and α = 0.2.

Accepted Answer

S₃ = 19.06

Question 5

A major drawback of the aggregate price index is that

Accepted Answer

A)  it does not take into account the fact that some items in the market basket are purchased more frequently than others. 
B)  it is difficult to compute. 
C)  it is computed by using the values from a single time series or based on a single product. 
D)  percentage comparisons cannot be made to the base year. 
A)  it does not take into account the fact that some items in the market basket are purchased more frequently than others. 
B)  it is difficult to compute. 
C)  it is computed by using the values from a single time series or based on a single product. 
D)  percentage comparisons cannot be made to the base year.

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

I_L₁₉₉₀ = 110.35

Question 7

Consider the following set of quarterly sales data given in thousands of dollars.   Write an appropriate dummy variable model that incorporates a linear trend and constant seasonal variation.

Accepted Answer

y(t)= B₀ + B₁_t + B_Q1(Q1)+ B_Q2(Q2)+ B_Q3(Q3)+ E_t The

Question 8

Using the price of the following food items,compute the aggregate index numbers for the four types of cheese.Let 1990 be the base year for this market basket of goods.

Accepted Answer

1990 = 100.0,1995 = 108.5,2000

Question 9

Removing the seasonal effect by dividing the actual time series observation by the estimated seasonal factor associated with the time series observation is called deseasonalization.

Accepted Answer

A) True 
 B)False

Question 10

Which of the following time series forecasting methods would not be used to forecast a time series that exhibits a linear trend with no seasonal or cyclical patterns?

Accepted Answer

A)  dummy variable regression 
B)  linear trend regression 
C)  Holt-Winters double exponential smoothing 
D)  multiplicative Winters method 
E)  both dummy variable regression and multiplicative Winters method 
A)  dummy variable regression 
B)  linear trend regression 
C)  Holt-Winters double exponential smoothing 
D)  multiplicative Winters method 
E)  both dummy variable regression and multiplicative Winters method

Question 11

Which of the following is not a component of time series?

Accepted Answer

A)  trend 
B)  seasonal 
C)  cyclical 
D)  irregular 
E)  smoothing constant 
A)  trend 
B)  seasonal 
C)  cyclical 
D)  irregular 
E)  smoothing constant

Question 12

A forecasting method that weights recent observations more heavily is called _____________.

Accepted Answer

A)  time series analysis 
B)  first-order autocorrelation 
C)  multiplicative decomposition 
D)  exponential smoothing 
A)  time series analysis 
B)  first-order autocorrelation 
C)  multiplicative decomposition 
D)  exponential smoothing

Question 13

Consider the quarterly production data (in thousands of units)for the XYZ manufacturing company below,followed by the centered moving average values and their respective periods..   Calculate the average seasonal factor for each quarter (  
).

Accepted Answer

winter = .986,spring = .915,summer = 1.1

Question 14

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 15

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

Accepted Answer

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

Question 16

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 17

Consider the following data and calculations.Calculate the estimated value of b1 and b0,and state the linear trend regression prediction equation.

Accepted Answer

Question 18

The multiplicative Winters' method used to forecast time series applies a seasonal factor SNT to the forecasting model..

Accepted Answer

A) True 
 B)False

Question 19

Three criteria used to compare two forecasting methods are the mean absolute deviation,the mean squared deviation,and the mean absolute percentage error.

Accepted Answer

A) True 
 B)False

Question 20

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.

Weighting in exponential smoothing is accomplished by using _____________.

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 average forecast error.

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 MAD.

Consider the following data. Calculate S₃ using simple exponential smoothing if S₁ = 18.6 and α = 0.2.

A major drawback of the aggregate price index is that

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.

Consider the following set of quarterly sales data given in thousands of dollars. Write an appropriate dummy variable model that incorporates a linear trend and constant seasonal variation.

Using the price of the following food items,compute the aggregate index numbers for the four types of cheese.Let 1990 be the base year for this market basket of goods.

Removing the seasonal effect by dividing the actual time series observation by the estimated seasonal factor associated with the time series observation is called deseasonalization.

Which of the following time series forecasting methods would not be used to forecast a time series that exhibits a linear trend with no seasonal or cyclical patterns?

Which of the following is not a component of time series?

A forecasting method that weights recent observations more heavily is called _____________.

Consider the quarterly production data (in thousands of units)for the XYZ manufacturing company below,followed by the centered moving average values and their respective periods.. Calculate the average seasonal factor for each quarter ( ).

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

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

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

Consider the following data and calculations.Calculate the estimated value of b₁ and b₀,and state the linear trend regression prediction equation.

The multiplicative Winters' method used to forecast time series applies a seasonal factor SN_T to the forecasting model..

Three criteria used to compare two forecasting methods are the mean absolute deviation,the mean squared deviation,and the mean absolute percentage error.

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

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

Weighting in exponential smoothing is accomplished by using _____________.

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 average forecast error.

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 MAD.

Consider the following data. Calculate S3 using simple exponential smoothing if S1 = 18.6 and α = 0.2.

A major drawback of the aggregate price index is that

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.

Consider the following set of quarterly sales data given in thousands of dollars. Write an appropriate dummy variable model that incorporates a linear trend and constant seasonal variation.

Using the price of the following food items,compute the aggregate index numbers for the four types of cheese.Let 1990 be the base year for this market basket of goods.

Removing the seasonal effect by dividing the actual time series observation by the estimated seasonal factor associated with the time series observation is called deseasonalization.

Which of the following time series forecasting methods would not be used to forecast a time series that exhibits a linear trend with no seasonal or cyclical patterns?

Which of the following is not a component of time series?

A forecasting method that weights recent observations more heavily is called _____________.

Consider the quarterly production data (in thousands of units)for the XYZ manufacturing company below,followed by the centered moving average values and their respective periods.. Calculate the average seasonal factor for each quarter ( ).

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

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

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

Consider the following data and calculations.Calculate the estimated value of b1 and b0,and state the linear trend regression prediction equation.

The multiplicative Winters' method used to forecast time series applies a seasonal factor SNT to the forecasting model..

Three criteria used to compare two forecasting methods are the mean absolute deviation,the mean squared deviation,and the mean absolute percentage error.

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

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

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 average forecast error.

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 MAD.

Consider the following data. Calculate S₃ using simple exponential smoothing if S₁ = 18.6 and α = 0.2.

Consider the following data and calculations.Calculate the estimated value of b₁ and b₀,and state the linear trend regression prediction equation.

The multiplicative Winters' method used to forecast time series applies a seasonal factor SN_T to the forecasting model..