Question 1

In situations where you need to compare forecasting methods for different time periods, the most appropriate accuracy measure is

Accepted Answer

A) mean error 
B) mean absolute error 
C) mean squared error 
D) mean absolute percentage error 
A) mean error 
B) mean absolute error 
C) mean squared error 
D) mean absolute percentage error

Question 2

The following linear trend expression was estimated using a time series with 17 time periods.Tt = 129.2 + 3.8t The trend projection for time period 18 is

Accepted Answer

A) 68.4 
B) 193.8 
C) 197.6 
D) 6.84 
A) 68.4 
B) 193.8 
C) 197.6 
D) 6.84

Question 3

A seasonal pattern

Accepted Answer

A) can occur within a day 
B) can take more than a year to repeat itself 
C) is a multi-year run of observations above and below the trend line 
D) reflects a shift in the time series over time 
A) can occur within a day 
B) can take more than a year to repeat itself 
C) is a multi-year run of observations above and below the trend line 
D) reflects a shift in the time series over time

Question 4

Below you are given the first two values of a time series. You are also given the first two values of the exponential smoothing forecast.   If the smoothing constant equals .3, then the exponential smoothing forecast for time period three is

Accepted Answer

A) 18 
B) 19.2 
C) 20 
D) 40 
A) 18 
B) 19.2 
C) 20 
D) 40

Question 5

If the estimate of the trend component is 158.2, the estimate of the seasonal component is 94%, the estimate of the cyclical component is 105%, and the estimate of the irregular component is 98%, then the multiplicative model will produce a forecast of

Accepted Answer

A) 1.53 
B) 1.53% 
C) 153.02 
D) 153,020,532 
A) 1.53 
B) 1.53% 
C) 153.02 
D) 153,020,532

Question 6

The time series pattern showing an alternating sequence of points below and above the trend line lasting more than one year is the

Accepted Answer

A) trend pattern 
B) seasonal pattern 
C) trend and seasonal pattern 
D) cyclical pattern 
A) trend pattern 
B) seasonal pattern 
C) trend and seasonal pattern 
D) cyclical pattern

Question 7

You are given the following information on the quarterly profits for Ajax Corporation.   
a.Find the four-quarter centered moving averages.
b.Compute the seasonal-irregular component.
c.Compute the seasonal factors for all four quarters.
d.Represent the deseasonalized series.

Accepted Answer

a.145, 146.25, 150, 153.75, 157.5, 161.2

Question 8

Exhibit 17-3
Consider the following time series.  
-The term exponential smoothing comes from

Accepted Answer

A) its emphasis on minimizing mean squared error 
B) the exponential nature of the weighting scheme used 
C) its use in fitting exponential trend lines 
D) the nonlinear noise it attempts to remove 
A) its emphasis on minimizing mean squared error 
B) the exponential nature of the weighting scheme used 
C) its use in fitting exponential trend lines 
D) the nonlinear noise it attempts to remove

Question 9

Below you are given the seasonal factors and the estimated trend equation for a time series. These values were computed on the basis of 5 years of quarterly data.   T = 126.23 - 1.6t
Produce forecasts for all four quarters of year 6 by using the seasonal and trend components.

Accepted Answer

111.156, 8

Question 10

Exhibit 17-3
Consider the following time series.  
-To calculate an exponential smoothing forecast of demand, what values are required?

Accepted Answer

A)  alpha, number of periods, last actual demand 
B)  alpha, last forecast, number of periods 
C)  alpha, last forecast, last actual demand 
D)  last forecast, number of periods, averaging period 
A)  alpha, number of periods, last actual demand 
B)  alpha, last forecast, number of periods 
C)  alpha, last forecast, last actual demand 
D)  last forecast, number of periods, averaging period

Question 11

The following information has been collected on the sales of greeting cards for the past 6 weeks.   
a.Produce exponential smoothing forecasts for the series using a smoothing constant of .2.
b.Compute the mean square error for the forecasts produced with a smoothing constant of .2.
c.What is the forecast of sales for week 7?
d.Is a smoothing constant of .2 or .3 better for the sales data? Explain.

Accepted Answer

a.105, 105, 102, 100

Question 12

The following time series shows the sales of a clothing store over a 10-week period.   
a.Compute a 4-week moving average for the above time series.
b.Compute the mean square error (MSE) for the 4-week moving average forecast.
c.Use $\alpha$ = 0.3 to compute the exponential smoothing values for the time series.
d.Forecast sales for week 11.

Accepted Answer

a.17, 18, 19, 19, 20, 19
b.7.6

Question 13

If data for a time series analysis is collected on an annual basis only, which pattern can be ignored?

Accepted Answer

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

Question 14

The following time series shows the number of units of a particular product sold over the past six months.   
a.Compute a 3-month moving average (centered) for the above time series.
b.Compute the mean square error (MSE) for the 3-month moving average.
c.Use $\alpha$ = 0.2 to compute the exponential smoothing values for the time series.
d.Forecast the sales volume for month 7.

Accepted Answer

a.5, 4, 7
b.MSE = 73

Question 15

The temperature in Chicago has been recorded for the past seven days. You are given the information below.   
a.Produce exponential smoothing forecasts for the series using a smoothing constant of .2.
b.Compute the mean square error for the forecasts produced with a smoothing constant of .2.
c.What is the forecasted temperature for day 8?
d.Is a smoothing constant of .2 or .3 better for the temperature data? Explain.

Accepted Answer

a.82, 81.6, 82.08, 82.264, 81.

Question 16

Which of the following smoothing constants would make an exponential smoothing forecast equivalent to a naive forecast?

Accepted Answer

A) 0 
B) 1 divided by the number of periods 
C) 0.5 
D) 1.0 
A) 0 
B) 1 divided by the number of periods 
C) 0.5 
D) 1.0

Question 17

Consider the following annual series on the number of people assisted by a county human resources department.   
a.Prepare 3-year moving average values to be used as forecasts for periods 4 through 11. Calculate the mean squared error (MSE) measure of forecast accuracy for periods 4 through 11.
b.
b.Use a smoothing constant of .4 to compute exponential smoothing values to be used as forecasts for periods 2 through 11. Calculate the MSE.
c.Compare the results in Parts a and

Accepted Answer

a.24.667, 25.333, 24.667, 23.333, 22, 23

Question 18

Common types of data patterns that can be identified when examining a time series plot include all of the following except

Accepted Answer

A) horizontal 
B) vertical 
C) seasonal 
D) cyclical 
A) horizontal 
B) vertical 
C) seasonal 
D) cyclical

Question 19

Exhibit 17-2
Consider the following time series.  
-Refer to Exhibit 17-2. The intercept, b0, is

Accepted Answer

A) 2.5 
B) 2.0 
C) 1.0 
D) 1.25 
A) 2.5 
B) 2.0 
C) 1.0 
D) 1.25

Question 20

The sales records of a company over a period of seven years are shown below.   
a.Develop a linear trend expression for the above time series.
b.Forecast sales for period 10.

Accepted Answer

a.T_t = 12 +

In situations where you need to compare forecasting methods for different time periods, the most appropriate accuracy measure is

The following linear trend expression was estimated using a time series with 17 time periods.T_t = 129.2 + 3.8t The trend projection for time period 18 is

A seasonal pattern

Below you are given the first two values of a time series. You are also given the first two values of the exponential smoothing forecast. If the smoothing constant equals .3, then the exponential smoothing forecast for time period three is

If the estimate of the trend component is 158.2, the estimate of the seasonal component is 94%, the estimate of the cyclical component is 105%, and the estimate of the irregular component is 98%, then the multiplicative model will produce a forecast of

The time series pattern showing an alternating sequence of points below and above the trend line lasting more than one year is the

You are given the following information on the quarterly profits for Ajax Corporation. a.Find the four-quarter centered moving averages. b.Compute the seasonal-irregular component. c.Compute the seasonal factors for all four quarters. d.Represent the deseasonalized series.

Exhibit 17-3 Consider the following time series. -The term exponential smoothing comes from

Below you are given the seasonal factors and the estimated trend equation for a time series. These values were computed on the basis of 5 years of quarterly data. T = 126.23 - 1.6t Produce forecasts for all four quarters of year 6 by using the seasonal and trend components.

Exhibit 17-3 Consider the following time series. -To calculate an exponential smoothing forecast of demand, what values are required?

If data for a time series analysis is collected on an annual basis only, which pattern can be ignored?

Which of the following smoothing constants would make an exponential smoothing forecast equivalent to a naive forecast?

Common types of data patterns that can be identified when examining a time series plot include all of the following except

Exhibit 17-2 Consider the following time series. -Refer to Exhibit 17-2. The intercept, b₀, is

The sales records of a company over a period of seven years are shown below. a.Develop a linear trend expression for the above time series. b.Forecast sales for period 10.

Data and Statistics

Descriptive Statistics: Tabular and Graphical Displays

Descriptive Statistics: Numerical Measures

Introduction to Probability

Discrete Probability Distributions

Continuous Probability Distributions

Sampling and Sampling Distributions

Interval Estimation

Hypothesis Tests

Inference About Means and Proportions With Two Populations

Inferences About Population Variances

Tests of Goodness of Fit, Independence and Multiple Proportions

Experimental Design and Analysis of Variance

Simple Linear Regression

Multiple Regression

Regression Analysis: Model Building

Nonparametric Methods

Statistical Methods for Quality Control

Decision Analysis

Sample Survey

Filters

Exam 17: Time Series Analysis and Forecasting

In situations where you need to compare forecasting methods for different time periods, the most appropriate accuracy measure is

The following linear trend expression was estimated using a time series with 17 time periods.Tt = 129.2 + 3.8t The trend projection for time period 18 is

A seasonal pattern

Below you are given the first two values of a time series. You are also given the first two values of the exponential smoothing forecast. If the smoothing constant equals .3, then the exponential smoothing forecast for time period three is

If the estimate of the trend component is 158.2, the estimate of the seasonal component is 94%, the estimate of the cyclical component is 105%, and the estimate of the irregular component is 98%, then the multiplicative model will produce a forecast of

The time series pattern showing an alternating sequence of points below and above the trend line lasting more than one year is the

You are given the following information on the quarterly profits for Ajax Corporation. a.Find the four-quarter centered moving averages. b.Compute the seasonal-irregular component. c.Compute the seasonal factors for all four quarters. d.Represent the deseasonalized series.

Exhibit 17-3 Consider the following time series. -The term exponential smoothing comes from

Below you are given the seasonal factors and the estimated trend equation for a time series. These values were computed on the basis of 5 years of quarterly data. T = 126.23 - 1.6t Produce forecasts for all four quarters of year 6 by using the seasonal and trend components.

Exhibit 17-3 Consider the following time series. -To calculate an exponential smoothing forecast of demand, what values are required?

If data for a time series analysis is collected on an annual basis only, which pattern can be ignored?

Which of the following smoothing constants would make an exponential smoothing forecast equivalent to a naive forecast?

Common types of data patterns that can be identified when examining a time series plot include all of the following except

Exhibit 17-2 Consider the following time series. -Refer to Exhibit 17-2. The intercept, b0, is

The sales records of a company over a period of seven years are shown below. a.Develop a linear trend expression for the above time series. b.Forecast sales for period 10.

Data and Statistics

Descriptive Statistics: Tabular and Graphical Displays

Descriptive Statistics: Numerical Measures

Introduction to Probability

Discrete Probability Distributions

Continuous Probability Distributions

Sampling and Sampling Distributions

Interval Estimation

Hypothesis Tests

Inference About Means and Proportions With Two Populations

Inferences About Population Variances

Tests of Goodness of Fit, Independence and Multiple Proportions

Experimental Design and Analysis of Variance

Simple Linear Regression

Multiple Regression

Regression Analysis: Model Building

Nonparametric Methods

Statistical Methods for Quality Control

Decision Analysis

Sample Survey

Filters

The following linear trend expression was estimated using a time series with 17 time periods.T_t = 129.2 + 3.8t The trend projection for time period 18 is

Exhibit 17-2 Consider the following time series. -Refer to Exhibit 17-2. The intercept, b₀, is