Question

The monthly sales for Yazici​ Batteries, Inc., were as​ follows:

                                                                                                                                         

Month

Jan

Feb

Mar

Apr

May

Jun

Jul

Aug

Sept

Oct

Nov

Dec

Sales

21

21

15

12

11

16

16

18

22

21

20

24

This exercise contains only parts b and c.

​b) The forecast for the next month​ (Jan) using the naive method​ =

nothing

sales ​(round your response to a whole​ number).

The forecast for the next period​ (Jan) using a​ 3-month moving average approach​ =

nothing

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

The forecast for the next period​ (Jan) using a​ 6-month weighted average with weights of

0.10​,

0.10​,

0.10​,

0.20​,

0.20​,

and

0.30​,

where the heaviest weights are applied to the most recent month​ =

nothing

sales ​(round your response to one decimal​ place).

Using exponential smoothing with

alphaα

​=

0.35

and a September forecast of

20.00​,

the forecast for the next period​ (Jan) =

nothing

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

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

nothing

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

​c) The method that can be used for making a forecast for the month of March is

▼

.

Answer 1

Answer b= The forecast for the next month​ (Jan) using the naive method​ =24

The forecast for the next period​ (Jan) using a​ 3-month moving average approach​ =(24+20+21)/3 =21.67

The forecast for the next period​ (Jan) using a​ 6-month weighted average=

(24*0.3+20*0.2+21*0.2+22*0.1+18*0.1+16*0.1)/(0.3+0.2+0.2+0.1+0.1+0.1) =21

For exponential forecast=

Forecast for October = 20+0.35*(22-20)=20.7

Forecast for November = 20.7+0.35*(21-20.7)=20.81

Forecast for December = 20.81+0.35*(20-20.81)=20.53

Forecast for January = 20.53+0.35*(24-20.53)=21.75

So the answer is=21.75

	x	y	x^2	x*y	y^2
	1	2	1	2	4
	2	21	4	42	441
	3	15	9	45	225
	4	12	16	48	144
	5	11	25	55	121
	6	16	36	96	256
	7	16	49	112	256
	8	18	64	144	324
	9	22	81	198	484
	10	21	100	210	441
	11	20	121	220	400
	12	24	144	288	576
Sum	78	198	650	1460	3672
	b = [(n* ∑xy ) - (∑x )*(∑y )] / [ (n* ∑x2 ) - ( ∑x )2
	b=((12*1460-78*198)/(12*650-78*78))
	b=1.21
	a = [ ∑y - (b* ∑x )] / n
	a=((198-1.21*78)/12
	a=8.64
	y=8.64+1.21x
	For January next year, x=13
	y=8.64+1.21*13
	y=24.37	so the forecast for January=24.37

Answer C- Trend projection model

Reason= With the help of trend projection forecasting method, we can predict the sales forecast of any time period and we have to put the value of x=15

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