Question 1

Use exponential smoothing with trend adjustment to forecast deliveries for period 10. Let alpha = 0.4, beta = 0.2, and let the initial trend value be 4 and the initial forecast be 200.
 $$\begin{array} { | c | c | } 
\hline &\text { Actual }\
\underline { \text { Period } } & \underline { \text { Detual } } \
\hline 1 & 200 \
\hline 2 & 212 \
\hline 3 & 214 \
\hline 4 & 222 \
\hline 5 & 236 \
\hline 6 & 221 \
\hline 7 & 240 \
\hline 8 & 244 \
\hline 9 & 250 \
\hline 10 & 266 \
\hline
\end{array}$$

Accepted Answer

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Question 2

What is the key difference between weighted moving average and simple moving average approaches to forecasting?

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Question 3

Weekly sales of copy paper at Cubicle Suppliers are in the table below. Compute a three-period moving average and a four-period moving average for weeks 5, 6, and 7. Compute MAD for each forecast. Which model is more accurate?
 Forecast week 8 with the more accurate method.
 $$\begin{array} { c c } 
\text { Week } & \text { Sales (cases) } \
\hline  2 & 17 \
2 & 21 \
3 & 27 \
4 & 31 \
5 & 19 \
6 & 17 \
7 & 21
\end{array}$$

Accepted Answer

The answer of Weekly sales of copy paper at Cubicle...

Question 4

Demand for a certain product is forecast to be 8,000 units per month, averaged over all 12 months of the year. The product follows a seasonal pattern, for which the January monthly index is 1.25. What is the seasonally-adjusted sales forecast for January?

Accepted Answer

The answer of Demand for a certain product is forecast...

Question 5

Marie Bain is the production manager at a company that manufactures hot water heaters. Marie needs a demand forecast for the next few years to help decide whether to add new production capacity. The company's sales history (in thousands of units) is shown in the table below. Use exponential smoothing with trend adjustment, to forecast demand for period 6. The initial forecast for period 1 was 11 units; the initial estimate of trend was 0. The smoothing constants are α = .3 and β = .3
 $$\begin{array} { | c | c | } 
\hline \text { Period } & \text { Actual } \
\hline 1 & 12 \
\hline 2 & 15 \
\hline 3 & 16 \
\hline 4 & 16 \
\hline 5 & 18 \
\hline 6 & 20 \
\hline
\end{array}$$

Accepted Answer

The answer of Marie Bain is the production manager at...

Question 6

Weekly sales of ten-grain bread at the local organic food market are in the table below. Based on this data, forecast week 9 using a five-week moving average.
$\begin{array}{ll}\text { Week }&\text { Sales }\
1 & 415 \
2 & 389 \
3 & 420 \
4 & 382 \
5 & 410 \
6 & 432 \
7 & 405 \
8 & 421
\end{array}$

Accepted Answer

The answer of Weekly sales of ten-grain bread at the...

Question 7

The quarterly sales for specific educational software over the past three years are given in the following table. Compute the four seasonal factors.
 $$\begin{array} { | c | c | c | c | } 
\hline & \text { YEAR 1 } & \text { YEAR 2 } & \text { YEAR 3 } \
\hline \text { Quarter 1 } & 1710 & 1820 & 1830 \
\hline \text { Quarter 2 } & 960 & 910 & 1090 \
\hline \text { Quarter 3 } & 2720 & 2840 & 2900 \
\hline \text { Quarter 4 } & 2430 & 2200 & 2590 \
\hline
\end{array}$$

Accepted Answer

The answer of The quarterly sales for specific educational software...

Question 8

A seasonal index for a monthly series is about to be calculated on the basis of three years' accumulation of data. The three previous July values were 110, 135, and 130. The average over all months is 160. The approximate seasonal index for July is:

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Question 9

What is the forecast for May based on a weighted moving average applied to the following past demand data and using the weights: 4, 3, 2 (largest weight is for most recent data)?
 $$\begin{array} { | l | l | l | l | l | l | } 
\hline \text { Nov. } & \text { Dec. } & \text { Tan. } & \text { Feb. } & \text { Mar. } & \text { April } \
\hline 37 & 36 & 40 & 42 & 47 & 43 \
\hline
\end{array}$$

Accepted Answer

The answer of What is the forecast for May based...

Question 10

A firm has modeled its experience with industrial accidents and found that the number of accidents per year (Y) is related to the number of employees (X) by the regression equation Y = 3.3 + 0.049*X. R-Square is 0.68. The regression is based on 20 annual observations. The firm intends to employ 480 workers next year. How many accidents do you project?
 How much confidence do you have in that forecast?

Accepted Answer

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Question 11

What is focus forecasting?

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Question 12

A small family-owned restaurant uses a seven-day moving average model to determine manpower requirements. These forecasts need to be seasonalized because each day of the week has its own demand pattern. The seasonal indices for each day of the week are: Monday, 0.445; Tuesday, 0.791; Wednesday, 0.927; Thursday, 1.033; Friday, 1.422; Saturday, 1.478; and Sunday 0.903. Average daily demand based on the most recent moving average is 194 patrons. What is the seasonalized forecast for each day of next week?

Accepted Answer

The answer of A small family-owned restaurant uses a seven-day...

Question 13

The last four weekly values of sales were 80, 100, 105, and 90 units. The last four forecasts (for the same four weeks) were 60, 80, 95, and 75 units. Calculate MAD, MSE, and MAPE for these four weeks.
 $$\begin{array} { | c | c | c | c | c | } 
\hline \text { Sales } & \text { Forecast } & \text { Error } & \text { Error squared } & \text { Pct. error } \
\hline 80 & 60 & 20 & 400 & .25 \
\hline 100 & 80 & 20 & 400 & .20 \
\hline 105 & 95 & 10 & 100 & .095 \
\hline 90 & 75 & 15 & 225 & .167 \
\hline
\end{array}$$

Accepted Answer

The answer of The last four weekly values of sales...

Question 14

Given the following data, calculate the three-year moving averages for years 4 through 10.
 $$\begin{array} { | c | c | } 
\hline \text { Year } & \text { Demand } \
\hline 1 & 74 \
\hline 2 & 90 \
\hline 3 & 59 \
\hline 4 & 91 \
\hline 5 & 140 \
\hline 6 & 98 \
\hline 7 & 110 \
\hline 8 & 123 \
\hline 9 & 99 \
\hline
\end{array}$$

Accepted Answer

The answer of Given the following data, calculate the three-year...

Question 15

A management analyst is using exponential smoothing to predict merchandise returns at an upscale branch of a department store chain. Given an actual number of returns of 154 items in the most recent period completed, a forecast of 172 items for that period, and a smoothing constant of 0.3, what is the forecast for the next period?
 How would the forecast be changed if the smoothing constant were 0.6?
 Explain the difference in terms of alpha and responsiveness.

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Question 16

What is a tracking signal?
 Explain the connection between adaptive smoothing and tracking signals.

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The answer of What is a tracking signal?
 Explain the...

Question 17

The following trend projection is used to predict quarterly demand: Y = 250 - 2.5t, where t = 1 in the first quarter. Seasonal (quarterly) indices are Quarter 1 = 1.5; Quarter 2 = 0.8; Quarter 3 = 1.1; and Quarter 4 = 0.6. What is the seasonally adjusted forecast for the next four quarters?

Accepted Answer

The answer of The following trend projection is used to...

Question 18

Favors Distribution Company purchases small imported trinkets in bulk, packages them, and sells them to retail stores. They are conducting an inventory control study of all their items. The following data are for one such item, which is not seasonal.
a. Use trend projection to estimate the relationship between time and sales (state the equation).
b. Calculate forecasts for the first four months of the next year.
 $$\begin{array} { | l | c | c | c | c | c | c | c | c | c | c | c | c | } 
\hline & 1 & 2 & 3 & 4 & 5 & 6 & 7 & 8 & 9 & 10 & 11 & 12 \
\hline \text { Month } & \text { Jan } & \text { Feb } & \text { Mar } & \text { Apr } & \text { May } & \text { Jun } & \text { Jul } & \text { Aug } & \text { Sep } & \text { Oct } & \text { Nov } & \text { Dec } \
\hline \text { Sales } & 51 & 55 & 54 & 57 & 50 & 68 & 66 & 59 & 67 & 69 & 75 & 73 \
\hline
\end{array}$$

Accepted Answer

The answer of Favors Distribution Company purchases small imported trinkets...

Question 19

A restaurant has tracked the number of meals served at lunch over the last four weeks. The data shows little in terms of trends, but does display substantial variation by day of the week. Use the following information to determine the seasonal (daily) index for this restaurant.
 $$\begin{array} { | l | l | l | l | l | } 
\hline & { \text { Week } } \
\hline \text { Day } & 1 & 2 & 3 & 4 \
\hline \text { Sunday } & 40 & 35 & 39 & 43 \
\hline \text { Monday } & 54 & 55 & 51 & 59 \
\hline \text { Tuesday } & 61 & 60 & 65 & 64 \
\hline \text { Wednesday } & 72 & 77 & 78 & 69 \
\hline \text { Thursday } & 89 & 80 & 81 & 79 \
\hline \text { Friday } & 91 & 90 & 99 & 95 \
\hline \text { Saturday } & 80 & 82 & 81 & 83 \
\hline
\end{array}$$

Accepted Answer

The answer of A restaurant has tracked the number of...

Question 20

Jim's department at a local department store has tracked the sales of a product over the last ten weeks. Forecast demand using exponential smoothing with an alpha of 0.4, and an initial forecast of 28.0 for period 1. Calculate the MAD. What do you recommend?
 $$\begin{array} { | c | c | } 
\hline \text { Period } & \text { Demand } \
\hline 1 & 24 \
\hline 2 & 23 \
\hline 3 & 26 \
\hline 4 & 36 \
\hline 5 & 26 \
\hline 6 & 30 \
\hline 7 & 32 \
\hline 8 & 26 \
\hline 9 & 25 \
\hline 10 & 28 \
\hline
\end{array}$$ 
 $\begin{array}{|c|c|l|l|l|l|}
\hline\begin{array}{c}
\text { Answer: } \
\text { Period }
\end{array} & \text { Demand } & \text { Forecast } & \text { Error } & & \text { Absolute } \\hline 1 & 24 & 28.00 & & & \
\hline 2 & 23 & 26.40 & -3.40 & & 3.40 \
\hline 3 & 26 & 25.04 & 0.96 & & 0.96 \
\hline 4 & 36 & 25.42 & 10.58 & & 10.58 \
\hline 5 & 26 & 29.65 & -3.65 & & 3.65 \
\hline 6 & 30 & 28.19 & 1.81 & & 1.81 \
\hline 7 & 32 & 28.92 & 3.08 & & 3.08 \\hline 8 & 26 & 30.15 & -4.15 & & 4.15 \
\hline 9 & 25 & 28.49 & -3.49 & & 3.49 \
\hline 10 & 28 & 27.09 & 0.91 & & 0.91 \
\hline & & \text { Total } & 2.64 & & 32.03 \
\hline & & \text { Average } & 0.29 & & 3.56 \
\hline & & & \text { Bias } & & \text { MAD } \
\hline
\end{array}$ 
The tracking signal RSFE/MAD = 2.64/3.56 = .742 is low; therefore, keep using the forecasting method.

Accepted Answer

The answer of Jim's department at a local department store...

Quiz 4: Forecasting

What is the key difference between weighted moving average and simple moving average approaches to forecasting?

Demand for a certain product is forecast to be 8,000 units per month, averaged over all 12 months of the year. The product follows a seasonal pattern, for which the January monthly index is 1.25. What is the seasonally-adjusted sales forecast for January?

Weekly sales of ten-grain bread at the local organic food market are in the table below. Based on this data, forecast week 9 using a five-week moving average. $\begin{array}{ll}\text { Week }&\text { Sales }\\1 & 415 \\2 & 389 \\3 & 420 \\4 & 382 \\5 & 410 \\6 & 432 \\7 & 405 \\8 & 421\end{array}$

A seasonal index for a monthly series is about to be calculated on the basis of three years' accumulation of data. The three previous July values were 110, 135, and 130. The average over all months is 160. The approximate seasonal index for July is:

What is focus forecasting?

What is a tracking signal? Explain the connection between adaptive smoothing and tracking signals.

The following trend projection is used to predict quarterly demand: Y = 250 - 2.5t, where t = 1 in the first quarter. Seasonal (quarterly) indices are Quarter 1 = 1.5; Quarter 2 = 0.8; Quarter 3 = 1.1; and Quarter 4 = 0.6. What is the seasonally adjusted forecast for the next four quarters?