Question 1

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

Accepted Answer

Question 2

The ___________ component of a time series consists of erratic and unsystematic fluctuations in the time series data.

Accepted Answer

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

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

Holt-Winters double exponential smoothing would be an appropriate method to use to forecast a time series that exhibits a linear trend with no seasonal or cyclical patterns.

Accepted Answer

A) True 
 B)False

Question 5

Consider the regression equation 
 = 6.04 + 0.10 (t)and the data below. 
Compute the residual (error term)for period 8.

Accepted Answer

The answer of Consider the regression equation 
 = 6.04...

Question 6

Suppose that the unadjusted seasonal factor for the month of April is 1.10.The sum of the 12 months' unadjusted seasonal factor values is 12.18.The normalized (adjusted)seasonal factor value for April

Accepted Answer

A)  is larger than 1.1. 
B)  is smaller than 1.1. 
C)  is equal to 1.1. 
D)  cannot be determined with the information provided. 
A)  is larger than 1.1. 
B)  is smaller than 1.1. 
C)  is equal to 1.1. 
D)  cannot be determined with the information provided.

Question 7

The multiplicative Winters method is used to forecast time series when there are no seasonal factors that are part of the model.

Accepted Answer

A) True 
 B)False

Question 8

A ___________ index is a weighted aggregate price index that uses the base period quantities as weights in all succeeding time periods.

Accepted Answer

A)  Paasche 
B)  first-order autocorrelation 
C)  Laspeyres 
D)  cyclical (seasonal) 
A)  Paasche 
B)  first-order autocorrelation 
C)  Laspeyres 
D)  cyclical (seasonal)

Question 9

Given the following data,compute the mean absolute deviation (MAD).

Accepted Answer

MAD = 24.3

Question 10

The ___________ component of a time series refers to the erratic time series movements that follow no recognizable or regular pattern.

Accepted Answer

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

Question 11

The basic difference between MAD and MSE is that MSE,unlike MAD,penalizes a forecasting technique much more for _________ errors than for _________ errors.

Accepted Answer

A)  large,small 
B)  small,large 
C)  small,zero 
D)  zero,large 
A)  large,small 
B)  small,large 
C)  small,zero 
D)  zero,large

Question 12

The linear trend equation for the following data is 
 = 1.4286 + 2.5(t). 
What is the predicted value of the fund in the period t = 1?

Accepted Answer

@#IMG-DLM&= 1.43 + 2

Question 13

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

Accepted Answer

MSD = 125

Question 14

Exponential smoothing is designed to forecast time series described by regular and seasonal components that are always changing over time.

Accepted Answer

A) True 
 B)False

Question 15

Two forecasting models were used to predict the future values of a time series.The forecasts are shown below with the actual values.   Which model is the most accurate? Why?

Accepted Answer

Model 2 is most accurate,becau

Question 16

A ____________ index is a weighted aggregate price index.It is accurate in its calculation of periodic prices.However,when using this index,it is difficult to compare the prices in different time periods.

Accepted Answer

A)  Paasche 
B)  first-order autocorrelation 
C)  Laspeyres 
D)  cyclical (seasonal) 
A)  Paasche 
B)  first-order autocorrelation 
C)  Laspeyres 
D)  cyclical (seasonal)

Question 17

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 18

The purpose behind moving averages and centered moving averages is to eliminate __________________.

Accepted Answer

A)  constant variation 
B)  cyclical variation 
C)  seasonal variation 
D)  regular variation 
A)  constant variation 
B)  cyclical variation 
C)  seasonal variation 
D)  regular variation

Question 19

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 a ___________ price index.

Accepted Answer

A)  Paasche 
B)  weighted aggregate 
C)  Laspeyres 
D)  cyclical (seasonal) 
A)  Paasche 
B)  weighted aggregate 
C)  Laspeyres 
D)  cyclical (seasonal)

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

The ___________ component of a time series consists of erratic and unsystematic fluctuations in the time series data.

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

Holt-Winters double exponential smoothing would be an appropriate method to use to forecast a time series that exhibits a linear trend with no seasonal or cyclical patterns.

Consider the regression equation = 6.04 + 0.10 (t)and the data below. Compute the residual (error term)for period 8.

Suppose that the unadjusted seasonal factor for the month of April is 1.10.The sum of the 12 months' unadjusted seasonal factor values is 12.18.The normalized (adjusted)seasonal factor value for April

The multiplicative Winters method is used to forecast time series when there are no seasonal factors that are part of the model.

A ___________ index is a weighted aggregate price index that uses the base period quantities as weights in all succeeding time periods.

Given the following data,compute the mean absolute deviation (MAD).

The ___________ component of a time series refers to the erratic time series movements that follow no recognizable or regular pattern.

The basic difference between MAD and MSE is that MSE,unlike MAD,penalizes a forecasting technique much more for _ errors than for _ errors.

The linear trend equation for the following data is = 1.4286 + 2.5(t). What is the predicted value of the fund in the period t = 1?

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

Exponential smoothing is designed to forecast time series described by regular and seasonal components that are always changing over time.

Two forecasting models were used to predict the future values of a time series.The forecasts are shown below with the actual values. Which model is the most accurate? Why?

A ____________ index is a weighted aggregate price index.It is accurate in its calculation of periodic prices.However,when using this index,it is difficult to compare the prices in different time periods.

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 5th and 6th years?

The purpose behind moving averages and centered moving averages is to eliminate __________________.

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 a ___________ price index.

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

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

The ___________ component of a time series consists of erratic and unsystematic fluctuations in the time series data.

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

Holt-Winters double exponential smoothing would be an appropriate method to use to forecast a time series that exhibits a linear trend with no seasonal or cyclical patterns.

Consider the regression equation = 6.04 + 0.10 (t)and the data below. Compute the residual (error term)for period 8.

Suppose that the unadjusted seasonal factor for the month of April is 1.10.The sum of the 12 months' unadjusted seasonal factor values is 12.18.The normalized (adjusted)seasonal factor value for April

The multiplicative Winters method is used to forecast time series when there are no seasonal factors that are part of the model.

A ___________ index is a weighted aggregate price index that uses the base period quantities as weights in all succeeding time periods.

Given the following data,compute the mean absolute deviation (MAD).

The ___________ component of a time series refers to the erratic time series movements that follow no recognizable or regular pattern.

The basic difference between MAD and MSE is that MSE,unlike MAD,penalizes a forecasting technique much more for _________ errors than for _________ errors.

The linear trend equation for the following data is = 1.4286 + 2.5(t). What is the predicted value of the fund in the period t = 1?

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

Exponential smoothing is designed to forecast time series described by regular and seasonal components that are always changing over time.

Two forecasting models were used to predict the future values of a time series.The forecasts are shown below with the actual values. Which model is the most accurate? Why?

A ____________ index is a weighted aggregate price index.It is accurate in its calculation of periodic prices.However,when using this index,it is difficult to compare the prices in different time periods.

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?

The purpose behind moving averages and centered moving averages is to eliminate __________________.

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 a ___________ price index.

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

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

The basic difference between MAD and MSE is that MSE,unlike MAD,penalizes a forecasting technique much more for _ errors than for _ errors.

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 5th and 6th years?