STATISTICAL TECHNIQUES FOR BUSINESS AND
STATISTICAL TECHNIQUES FOR BUSINESS AND
17th Edition
ISBN: 9781307261158
Author: Lind
Publisher: MCG/CREATE
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Chapter 18, Problem 28CE

a.

To determine

Determine the typical seasonal patterns for sales using the ratio-to-moving-average method.

a.

Expert Solution
Check Mark

Answer to Problem 28CE

The typical seasonal patterns for sales are 1.191168, 1.121778, 0.435094 and 1.251959, respectively.

Explanation of Solution

Calculation:

Four-Year moving average:

Four-year moving average=sum of the four concequent Sales4

Centered Moving Average:

Centered moving average=sum of the two concequent moving averages2

Specific seasonal index:

Specific seasonal index=SalesCentered moving average

YearQuarterVisitors

Four-quarter

moving average

Centered

Moving average

Specific seasonal
20101210
2180
360174.50.34384
4246174179.51.370474
20111214175186.751.145917
2216184187.51.152
382189.5189.50.432718
4230185.51951.179487
20121246193.5197.6251.244782
2228196.52051.112195
391198.75212.750.427732
4280211.252171.290323
20131258214.25222.51.159551
2250219.75227.51.098901
3113225.25232.3750.486283
4298229.75237.1251.256721
20141279235239.6251.164319
2267239.25240.751.109034
3116240244.3750.47468
4304241.5250.1251.215392
20151302247.25252.751.194857
2290253253.251.145114
3114252.5256.3750.444661
4310254258.8751.197489
20161321258.75259.751.235804
2291259261.751.111748
3120260.5
4320263

The Quarterly indexes are,

IIIIIIIV
20100.343841.370474
20111.1459171.1520.4327181.179487
20121.2447821.1121950.4277321.290323
20131.1595511.0989010.4862831.256721
20141.1643191.1090340.474681.215392
20151.1948571.1451140.4446611.197489
20161.2358041.111748
Mean1.1908711.1214990.4349861.251648

Typical Seasonal index:

Seasonal Index=Mean of the quarter×Correction Factor

Here, Correction Factor=4Sum of the means of the quarters.

Therefore,

Correction Factor=43.999003=1.000249

The seasonal indexes are,

IIIIIIIV
20100.343841.370474
20111.1459171.1520.4327181.179487
20121.2447821.1121950.4277321.290323
20131.1595511.0989010.4862831.256721
20141.1643191.1090340.474681.215392
20151.1948571.1451140.4446611.197489
20161.2358041.111748
Mean1.1908711.1214990.4349861.251648
Typical Seasonal Index1.1911681.1217780.4350941.251959

b.

To determine

Determine the trend equation.

b.

Expert Solution
Check Mark

Answer to Problem 28CE

The trend equation is Y^=163.57978+4.13473t.

Explanation of Solution

Calculation:

Deseasonalization:

Deseasonalization=Original salesTypical Index values

SalesTypical seasonal indexDeseasonalized Sales
2101.191168176.29755
1801.121778160.4595562
600.435094137.9012351
2461.251959196.4920576
2141.191168179.6555985
2161.121778192.5514674
820.435094188.4650214
2301.251959183.7120864
2461.191168206.5199871
2281.121778203.2487711
910.435094209.1502066
2801.251959223.6494965
2581.191168216.5941328
2501.121778222.8604947
1130.435094259.7139928
2981.251959238.0269641
2791.191168234.2238878
2671.121778238.0150083
1160.435094266.6090546
3041.251959242.8194534
3021.191168253.5326671
2901.121778258.5181738
1140.435094262.0123468
3101.251959247.6119426
3211.191168269.4833978
2911.121778259.4096158
1200.435094275.8024703
3201.251959255.5994246

Assign t value as 1 for first quarter of 2010, 2 for the second quarter of 2011 and so on.

Step-by-step procedure to obtain the regression using the Excel:

  • Enter the data for Sales and t in Excel sheet.
  • Go to Data Menu.
  • Click on Data Analysis.
  • Select ‘Regression’ and click on ‘OK’
  • Select the column of Deseasonalized Sales under ‘Input Y Range’.
  • Select the column of t under ‘Input X Range’.
  • Click on ‘OK’.

Output for the Regression obtained using the Excel is as follows:

STATISTICAL TECHNIQUES FOR BUSINESS AND, Chapter 18, Problem 28CE

From the Excel output, the regression equation is Y^=163.57978+4.13473t.

c.

To determine

Project the sales for the four quarters of next year using the trend equation.

Find the seasonally adjusted values.

c.

Expert Solution
Check Mark

Answer to Problem 28CE

The sales for the four quarters for next year are 283.487, 287.6217, 291.7564 and 295.8911.

The seasonally adjusted values are 337.6806, 322.6477, 126.9415 and 370.4435.

Explanation of Solution

Calculation:

From the output, the regression equation is Y^=163.57978+4.13473t.

The t value for first quarter of 2017 is 29.

Y^=163.57978+4.13473t=163.57978+(4.13473×29)=283.487

The t value for second quarter of 2017 is 30.

Y^=163.57978+4.13473t=163.57978+(4.13473×30)=287.6217

The t value for third quarter of 2017 is 31.

Y^=163.57978+4.13473t=163.57978+(4.13473×31)=291.7564

The t value for fourth quarter of 2017 is 32.

Y^=163.57978+4.13473t=163.57978+(4.13473×32)=295.8911

Seasonally Adjusted Forecast:

Estimated VisitorsSeasonal IndexForecast=Estimated Visitors×Seasonal Index
283.4871.191168337.6806
287.62171.121778322.6477
291.75640.435094126.9415
295.89111.251959370.4435

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