An electrical contractor's records during the last five weeks indicate the number of job requests:

Week:	1	2	3	4	5
Requests:	26	26	20	25	28

Predict the number of requests for week 6 using each of these methods:

a. Naive.

Number of requests

b. A four-period moving average. (Round your answer to 2 decimal places.) Number of requests c. Exponential smoothing with = .15. Use 25 for week 2 forecast. (Use the given week 2 forecast value in your calculation for the week 3 forecast. Then continue on, forecasting through week 6. Round your intermediate forecast values and final answer to 2 decimal places.)

	Number of Requests
F3
F4
F5
F6

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National Scan, Inc., sells radio frequency inventory tags. Monthly sales for a seven-month period were as follows:

Month	Sales (000)Units
Feb.	20
Mar.	23
Apr.	7
May.	25
Jun.	18
Jul.	28
Aug.	30

b. Forecast September sales volume using each of the following:

(1) A linear trend equation.(Round your intermediate calculations and final answer to 2 decimal places.) Yt thousands

(2) A five-month moving average. (Round your answer to 2 decimal places.)

Moving average thousands

(3) Exponential smoothing with a smoothing constant equal to .20, assuming a March forecast of 18(000). (Use the given March forecast value in your April forecast calculation, and continue forward from there, forecasting through September. Round intermediate forecast values and final answer to 2 decimal places) Forecast thousands

(4) The naive approach.

Naive approach thousands

(5) A weighted average using .60 for August, .20 for July, and .20 for June. (Round your answer to 2 decimal places.)

Weighted average thousands ----------------------------------------------------------

An analyst must decide between two different forecasting techniques for weekly sales of roller blades: a linear trend equation and the naive approach.

Linear trend: The linear trend equation is F_t = 125 + 2.2t. This equation was developed from data in periods 1 through 10. Use this equation to forecast periods 11 through 20. Then, based on actual data for periods 11 through 20 in the table below, calculate MAD and MSE for those periods.

Naive: Using periods 11 through 20, develop a naive forecast. Then caculate MAD and MSE for naive.

Enter your final answers in the second table below. (Round intermediate calculations and final answers to 2 decimal places.)

t	Units Sold
11	144
12	148
13	151
14	147
15	154
16	149
17	154
18	156
19	158
20	163

MAD (Naive)	37 Numeric ResponseEdit Unavailable. 37 incorrect.
MAD (Linear)	61.8 Numeric ResponseEdit Unavailable. 61.8 incorrect.
MSE (Naive)	173 Numeric ResponseEdit Unavailable. 173 incorrect.
MSE (Linear)	495.16 Numeric ResponseEdit Unavailable. 495.16 incorrect.

Which of these two methods has the greater accuracy if MAD and MSE are used?

provides forecasts with less average error and less average squared error.