Question

In: Operations Management

Month Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec Sales 19 23...

Month

Jan

Feb

Mar

Apr

May

Jun

Jul

Aug

Sept

Oct

Nov

Dec

Sales

19

23

15

14

13

16

15

17

19

20

20

23

Using a method of trend​ projection, the forecast for the next month​ (Jan) =

nothing

sales ​(round your response to two decimal​ places).

Solutions

Expert Solution

Month period(X) sales(Y) XY X^2(square of X)

Jan. 1 19 19 1

Feb 2 23 46 4

Mar 3 15 45 9

Apr 4 14. 56. 16

May. 5. 13. 65. 25

June. 6. 16. 96. 36

July. 7. 15. 105. 49

Aug. 8. 17. 136. 64

Sept. 9. 19. 171. 81

Oct. 10. 20. 200. 100

Nov. 11. 20. 220. 121

Dec. 12. 23. 276. 144

X = 1+2+3+4+5+6+7+8+9+10+11+12 = 78

Y = 19+23+15+14+13+16+15+17+19+20+20+23 = 214

XY = 19+46+45+56+65+96+105+136+171+200+220+276 = 1435

X^2 = 1+4+9+16+25+36+49+64+81+100+121+144 = 650

Number of periods = n = 12

X-bar = X/n = 78/12 = 6.5

Y-bar = Y/n = 214/12 = 17.83

b = [ XY - (n. X-bar. Y-bar)] / [ X^2 - (n. Square of X-bar)]

= [1435 - (12 x 6.5 x 17.83333333)] / [650 - (12 x 6.5 x 6.5)]

= (1435 - 1391)/(650-507)

= 44/143

= 0.31

a = Y-bar - (b. X-bar) = 17.83333333 - (0.31 x 6.5) = 17.83333333-2.015 = 15.82

So the regression equation is Y = a+bx => Y = 15.82+0.31x

Where x = sequential number of the year.

January is period 13. So for January,value of x = 13.so the forecast for January = 15.82+0.31x = 15.82+(0.31x13) = 15.82+4.03 = 19.85


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