Question 1

Statistical forecasting is based upon the assumption that the future will be an extrapolation of the past.

Accepted Answer

A) True 
 B)False

Question 2

MAD, MSE, and MAPE forecast error metrics generally give similar numerical results so it doesn't matter which one is used.

Accepted Answer

A) True 
 B)False

Question 3

A major difference between forecast accuracy measures MAD and MSE is that MAD is influenced much more by large forecast errors than by small errors.

Accepted Answer

A) True 
 B)False

Question 4

If single exponential smoothing is used and the time series has a negative trend, the forecast will

Accepted Answer

A) Lag 
B) Overshoot 
C) Be on target 
D) Have a MAD equal to zero 
A) Lag 
B) Overshoot 
C) Be on target 
D) Have a MAD equal to zero

Question 5

A tracking signal provides a method for quantifying forecast

Accepted Answer

A) bias 
B) error 
C) accuracy 
D) outliers 
A) bias 
B) error 
C) accuracy 
D) outliers

Question 6

In an exponential smoothing model, larger values of alpha i.e., closer to 1) place less emphasis on recent data and more on older data.

Accepted Answer

A) True 
 B)False

Question 7

Using the data shown below, compute the mean square error, mean absolute deviation, and mean absolute percentage error for the forecasts shown.
 $$\begin{array} { c c c } 
\text { Month } & \text { Forecast Demand } & \text { Actual Demand } \
\hline\text { April }& 170 & 180 \
\text { May } & 225 & 200 \
\text { Jure } & 210 & 200 \
\text { July } & 260 & 240 \
\text { August } & 200 & 230
\end{array}$$

Accepted Answer

Mean square error = [(180 - 170)^2</

Question 8

Better operational decisions can be made by integrating forecasting with value chain and capacity management systems.

Accepted Answer

A) True 
 B)False

Question 9

Aggregate forecasts are generally much easier to develop whereas detailed forecasts require more time and resources.

Accepted Answer

A) True 
 B)False

Question 10

Repeatable periods of ups and downs over short periods of time are called ____.

Accepted Answer

A) Trends 
B) Seasonal patterns 
C) Cyclical patterns 
D) Irregular variation 
A) Trends 
B) Seasonal patterns 
C) Cyclical patterns 
D) Irregular variation

Question 11

What is a time series, and what types of characteristics typically make up time series?

Accepted Answer

A time series is a set of observations m

Question 12

For single exponential smoothing,

Accepted Answer

A) Large values of alpha $\alpha$) place more emphasis on recent data 
B) Small values of alpha $\alpha$) place more emphasis on recent data 
C) Very volatile time series with substantial random variability should use a large value for alpha $\alpha$) 
D) Very stable time series with little random variability should use small values for alpha $\alpha$) 
A) Large values of alpha $\alpha$) place more emphasis on recent data 
B) Small values of alpha $\alpha$) place more emphasis on recent data 
C) Very volatile time series with substantial random variability should use a large value for alpha $\alpha$) 
D) Very stable time series with little random variability should use small values for alpha $\alpha$)

Question 13

Regular patterns in a data series that take place over long periods of time are called ____.

Accepted Answer

A) Trends 
B) Seasonal patterns 
C) Cyclical patterns 
D) Irregular variation 
A) Trends 
B) Seasonal patterns 
C) Cyclical patterns 
D) Irregular variation

Question 14

In practice, managers rely almost exclusively on statistical forecasts.

Accepted Answer

A) True 
 B)False

Question 15

The smoothing constant, $\alpha$, used in the basic exponential smoothing model, can range in value from -1 to +1.

Accepted Answer

A) True 
 B)False

Question 16

Define regression analysis and explain how it is an approach to forecasting.

Accepted Answer

Regression Analysis is a method for buil

Question 17

Sales of a new CD at a store for the last 4 weeks are shown below.
 $$\begin{array} { l c c c c } 
\text { Week } & 1 & 2 & 3 & 4 \
\text { Seles } & 112 & 105 & 125 & 118
\end{array}$$ 
a.Find a 3 period moving average forecast for the next week.
b.Find a 4 period moving average forecast for the next week.
c.Actual sales for week 5 were 105 units. What would be the 3- and 4-period moving average forecasts for week 6?

Accepted Answer

a.(105 + 125 + 118)/3 = 116
b.

Question 18

Describe some of the issues that managers must consider in applying forecasting methods in practice.

Accepted Answer

In practice, managers use a variety of j

Question 19

Based on the information shown below, develop forecasts for June using both a 2-period moving average model and an exponential smoothing model with $\alpha$ = 0.10. For the exponential smoothing model, assume the forecast for February was 800.
 $\begin{array}{cc}
\text { Month } & \text { Actual Demand } \
\hline \text { February } & 850 \
\text { March } & 900 \
\text { April } & 975 \
\text { May } & 950
\end{array}$

Accepted Answer

To develop forecasts for June using a 2-

Question 20

In a regression model, both the dependent and independent variables must be numerical.

Accepted Answer

A) True 
 B)False

Exam 11: Forecasting and Demand Planning

Statistical forecasting is based upon the assumption that the future will be an extrapolation of the past.

MAD, MSE, and MAPE forecast error metrics generally give similar numerical results so it doesn't matter which one is used.

A major difference between forecast accuracy measures MAD and MSE is that MAD is influenced much more by large forecast errors than by small errors.

If single exponential smoothing is used and the time series has a negative trend, the forecast will

A tracking signal provides a method for quantifying forecast

In an exponential smoothing model, larger values of alpha i.e., closer to 1) place less emphasis on recent data and more on older data.

Using the data shown below, compute the mean square error, mean absolute deviation, and mean absolute percentage error for the forecasts shown. Month Forecast Demand Actual Demand April 170 180 May 225 200 Jure 210 200 July 260 240 August 200 230

Better operational decisions can be made by integrating forecasting with value chain and capacity management systems.

Aggregate forecasts are generally much easier to develop whereas detailed forecasts require more time and resources.

Repeatable periods of ups and downs over short periods of time are called ____.

What is a time series, and what types of characteristics typically make up time series?

For single exponential smoothing,

Regular patterns in a data series that take place over long periods of time are called ____.

In practice, managers rely almost exclusively on statistical forecasts.

The smoothing constant, α\alphaα , used in the basic exponential smoothing model, can range in value from -1 to +1.

Define regression analysis and explain how it is an approach to forecasting.

Describe some of the issues that managers must consider in applying forecasting methods in practice.

In a regression model, both the dependent and independent variables must be numerical.

Goods, Services, and Operations Management

Value Chains

Measuring Performance in Operations

Operations Strategy

Technology and Operations Management

Goods and Service Design

Process Selection, Design, and Analysis

Facility and Work Design

Supply Chain Design

Capacity Management

Managing Inventories

Resource Management

Operations Scheduling and Sequencing

Quality Management

Quality Control and Spc

Lean Operating Systems

Project Management

Work Measurement, Learning Curves, and Standards

Queuing Analysis

Modeling Using Linear Programming

Simulation

Work Measurement, Learning Curves, and Standards

Filters

The smoothing constant, $\alpha$ , used in the basic exponential smoothing model, can range in value from -1 to +1.