Question 1

Using a naive forecasting method, the forecast for next week's sales volume equals

Accepted Answer

A)  the most recent week's sales volume 
B)  the most recent week's forecast 
C)  the average of the last four weeks' sales volumes 
D)  next week's production volume 
A)  the most recent week's sales volume 
B)  the most recent week's forecast 
C)  the average of the last four weeks' sales volumes 
D)  next week's production volume

Question 2

If the random variability in a time series is great, a high α value should be used to exponentially smooth out the fluctuations.

Accepted Answer

A) True 
 B)False

Question 3

Describe a time series plot and discuss its purpose and when in the forecasting process it should be constructed.​

Accepted Answer

A time series plot is a graphical repres

Question 4

A time series model with a seasonal pattern will always involve quarterly data.

Accepted Answer

A) True 
 B)False

Question 5

All of the following are true about time series methods except

Accepted Answer

A)  They discover a pattern in historical data and project it into the future. 
B)  They involve the use of expert judgment to develop forecasts. 
C)  They assume that the pattern of the past will continue into the future. 
D)  Their forecasts are based solely on past values of the variable or past forecast errors. 
A)  They discover a pattern in historical data and project it into the future. 
B)  They involve the use of expert judgment to develop forecasts. 
C)  They assume that the pattern of the past will continue into the future. 
D)  Their forecasts are based solely on past values of the variable or past forecast errors.

Question 6

Forecast errors

Accepted Answer

A)  are the difference in successive values of a time series 
B)  are the differences between actual and forecast values 
C)  should all be nonnegative 
D)  should be summed to judge the goodness of a forecasting model 
A)  are the difference in successive values of a time series 
B)  are the differences between actual and forecast values 
C)  should all be nonnegative 
D)  should be summed to judge the goodness of a forecasting model

Question 7

How can error measures be used to determine the number of periods to use in a moving average? What are you
assuming about the future when you make this choice?​

Accepted Answer

Error measures can be used to determine

Question 8

The number of girls who attend a summer basketball camp has been recorded for the seven years the camp has been offered. Use exponential smoothing with a smoothing constant of .8 to forecast attendance for the eighth year.
47, 68, 65, 92, 98, 121, 146

Accepted Answer

FORECASTING WITH EXPONENTIAL S

Question 9

One measure of the accuracy of a forecasting model is the

Accepted Answer

A)  smoothing constant 
B)  linear trend 
C)  mean absolute error 
D)  seasonal index 
A)  smoothing constant 
B)  linear trend 
C)  mean absolute error 
D)  seasonal index

Question 10

The exponential smoothing forecast for any period is a weighted average of all the previous actual values for the time series.

Accepted Answer

A) True 
 B)False

Question 11

Time series methods base forecasts only on past values of the variables.

Accepted Answer

A) True 
 B)False

Question 12

The number of pizzas ordered on Friday evenings between 5:30 and 6:30 at a pizza delivery location for the last 10 weeks is shown below. Use exponential smoothing with smoothing constants of .2 and .8 to forecast a value for week 11. Compare your forecasts using MSE. Which smoothing constant would you prefer?
58, 46, 55, 39, 42, 63, 54, 55, 61, 52

Accepted Answer

FORECASTING WITH EXPONENTIAL SMOOTHING
*

Question 13

Which of the following forecasting methods puts the least weight on the most recent time series value?

Accepted Answer

A)  exponential smoothing with α = .3 
B)  exponential smoothing with α = .2 
C)  moving average using the most recent 4 periods 
D)  moving average using the most recent 3 periods 
A)  exponential smoothing with α = .3 
B)  exponential smoothing with α = .2 
C)  moving average using the most recent 4 periods 
D)  moving average using the most recent 3 periods

Question 14

Seasonal patterns

Accepted Answer

A)  cannot be predicted. 
B)  are regular repeated patterns. 
C)  are multiyear runs of observations above or below the trend line. 
D)  reflect a shift in the time series over time. 
A)  cannot be predicted. 
B)  are regular repeated patterns. 
C)  are multiyear runs of observations above or below the trend line. 
D)  reflect a shift in the time series over time.

Question 15

All quarterly time series contain seasonality.

Accepted Answer

A) True 
 B)False

Question 16

Explain and contrast three measures of forecast accuracy.​

Accepted Answer

There are several measures of forecast a

Question 17

The number of plumbing repair jobs performed by Auger's Plumbing Service in each of the last nine months are listed below.   ​ 
a.Assuming a linear trend function, forecast the number of repair jobs Auger's will perform in December using the least squares method.
b.What is your forecast for December using a three-period weighted moving average with weights of .6, .3, and .1? How does it compare with your forecast from part (a)?

Accepted Answer

a.Ȳ₁₀ = 349.667 + (1

Question 18

Explain what conditions make quantitative forecasting methods appropriate.​

Accepted Answer

Quantitative forecasting methods are app

Question 19

Business at Terry's Tie Shop can be viewed as falling into three distinct seasons: (1) Christmas (November-December); (2) Father's Day (late May - mid-June); and (3) all other times. Average weekly sales (in $'s) during each of these three seasons during the past four years has been as follows:   ​
Determine a forecast for the average weekly sales in years 5 and 6 for each of the three seasons.

Accepted Answer

Ȳ_t = 797 + 1095.433S1_t + 1189.46

Question 20

Linear trend is calculated as   . The trend projection for period 15 is

Accepted Answer

A)  11.25 
B)  28.50 
C)  39.75 
D)  44.25 
A)  11.25 
B)  28.50 
C)  39.75 
D)  44.25

Using a naive forecasting method, the forecast for next week's sales volume equals

If the random variability in a time series is great, a high α value should be used to exponentially smooth out the fluctuations.

Describe a time series plot and discuss its purpose and when in the forecasting process it should be constructed.

A time series model with a seasonal pattern will always involve quarterly data.

All of the following are true about time series methods except

Forecast errors

How can error measures be used to determine the number of periods to use in a moving average? What are you assuming about the future when you make this choice?

The number of girls who attend a summer basketball camp has been recorded for the seven years the camp has been offered. Use exponential smoothing with a smoothing constant of .8 to forecast attendance for the eighth year. 47, 68, 65, 92, 98, 121, 146

One measure of the accuracy of a forecasting model is the

The exponential smoothing forecast for any period is a weighted average of all the previous actual values for the time series.

Time series methods base forecasts only on past values of the variables.

Which of the following forecasting methods puts the least weight on the most recent time series value?

Seasonal patterns

All quarterly time series contain seasonality.

Explain and contrast three measures of forecast accuracy.

Explain what conditions make quantitative forecasting methods appropriate.

Linear trend is calculated as . The trend projection for period 15 is

Introduction

An Introduction to Linear Programming

Linear Programming: Sensitivity Analysis and Interpretation of Solution

Linear Programming Applications in Marketing, Finance, and Operations Management

Advanced Linear Programming Applications

Distribution and Network Models

Integer Linear Programming

Nonlinear Optimization Models

Project Scheduling: Pertcpm

Inventory Models

Waiting Line Models

Simulation

Decision Analysis

Multicriteria Decisions

Markov Processes

Linear Programming: Simplex Method

Simplex-Based Sensitivity Analysis and Duality

Solution Procedures for Transportation and Assignment Problems

Minimal Spanning Tree

Dynamic Programming

Filters

Exam 15: Time Series Analysis and Forecasting

Using a naive forecasting method, the forecast for next week's sales volume equals

If the random variability in a time series is great, a high α value should be used to exponentially smooth out the fluctuations.

Describe a time series plot and discuss its purpose and when in the forecasting process it should be constructed.​

A time series model with a seasonal pattern will always involve quarterly data.

All of the following are true about time series methods except

Forecast errors

How can error measures be used to determine the number of periods to use in a moving average? What are you assuming about the future when you make this choice?​

The number of girls who attend a summer basketball camp has been recorded for the seven years the camp has been offered. Use exponential smoothing with a smoothing constant of .8 to forecast attendance for the eighth year. 47, 68, 65, 92, 98, 121, 146

One measure of the accuracy of a forecasting model is the

The exponential smoothing forecast for any period is a weighted average of all the previous actual values for the time series.

Time series methods base forecasts only on past values of the variables.

Which of the following forecasting methods puts the least weight on the most recent time series value?

Seasonal patterns

All quarterly time series contain seasonality.

Explain and contrast three measures of forecast accuracy.​

Explain what conditions make quantitative forecasting methods appropriate.​

Linear trend is calculated as . The trend projection for period 15 is

Introduction

An Introduction to Linear Programming

Linear Programming: Sensitivity Analysis and Interpretation of Solution

Linear Programming Applications in Marketing, Finance, and Operations Management

Advanced Linear Programming Applications

Distribution and Network Models

Integer Linear Programming

Nonlinear Optimization Models

Project Scheduling: Pertcpm

Inventory Models

Waiting Line Models

Simulation

Decision Analysis

Multicriteria Decisions

Markov Processes

Linear Programming: Simplex Method

Simplex-Based Sensitivity Analysis and Duality

Solution Procedures for Transportation and Assignment Problems

Minimal Spanning Tree

Dynamic Programming

Filters

Describe a time series plot and discuss its purpose and when in the forecasting process it should be constructed.

How can error measures be used to determine the number of periods to use in a moving average? What are you assuming about the future when you make this choice?

Explain and contrast three measures of forecast accuracy.

Explain what conditions make quantitative forecasting methods appropriate.