Quantitative Methods

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1a2 CHAPTER5 ' FORECASTING

, 5-11 l)ata collectcti on thc yearly clemanil lbr 50-pouncl

tt hns oi t'c'titi"crut W'll'ict Gardcn Supply are

'r'i'i*n"i" tn" ibllowing table' Develop.a

3-year mov-

ing averaee to'fo'"tuJ'sales' Then estinrate derntrnd

again with " *"ig*A *'"irr*-1:::1ge in which

saiesinthemost,i""n.y"u.aregivenau'eightof2 anrl sales i" tLt tltt* i lla's u'e each

givcn a weight

of 1' Which method do you think is best'l

5-23 What el ct ilicl the smoothing cr:rnstanttave on tlre

forccasl lt" Cooi-ttt'n air conditioners ? S:::.:::;

iH:i:;;;il-" I whrch srnr2thins c()nstarrt gircsthe m()stllucurilt('iorecast' . - .:^^ -.,,,t,.1

OTTTIANN TON FERTILIZER

5-24 LIsc a thrcc-yelr movitlg avcr'agc lorcca

to forecast the\alcs otto<il-Man air conditiotrers

lsee Problem 5-$)'

5-25 Using thc trend Jtroiection rnl-th()d' derelop a I'ore-

casting *"dt1 ;..]; it ':1:' of Cool-Man irir condi-

tione.i (see Problem 5-21)'

5-26 woultl you r'r'se exponential ::']:l:]:"*,,y1*: ,*""'i"1* Ln','n' oI0'l' a 3 ITt'::)lls l-":::;: ..;;';;;";;:* preclict thd sales :l c-"'l;M1", irtonor- ;ffi'/:-;;;t" p"'tri*' 5'21'5-24' and 5-2-s'

5-2'7 Salers'of industrial vacuum cleaners at R' Lowenthal

)-^!' t iffi,, ai"' "'"t tt'"

pott 13 months are as follows:

:c forccasting nrodel

($1,000s) MONTH

August

Septembet

SALES ($1'000s)

11

14

16

10

15

11

11

YEAR (1,000s Of'BAGS)

1

2

3

.t

5

6

't

8

4

6

4

5

l0 8

1

9

12

l4

15

1l

14

16

l1

-%ibrt'crtiliz.,ri, Dcvc,loP a trcnd line for r

Problem 5-'l7, using an,v computer to'.t:1tt'

. ,..--.. tn Pr,,hlcrq 5-17 ;tntl 5-ls.frec I'i'tt::-:'f::t:.

,,p::; io, tFld"*und tl"'":lllll:lcasts wcre

May

Junc

JulY

(a) Using a movi delermine the

next February'

C)ctober

threc Pcriods, uum cleaners lor

$.s-ra

: 5-19

< 11

a weighted nnd u t."n,l line' Which (b) Using a weightcd

g average with three

,,n" *rul.l you usef 'Qxplain

'vour answer' e demand

for vacuum I-]se 3, 2, and 1 for the

$: s-20 i, r. "^n"".rrrti'* o Jlqln g *] th "l':1.:,1111:, :::;

cleaners 1'or t. second most recent'

weights of the and third most cxamPlc. if for of l. January

(c) (d) What

inf sales'l

YEAR SALES

I

2

3

4

5

6

for the Past 12 weeks:

ACTUAL PASSENGER ACTUALPASSENGER

WEEK MILES O WEEK (1,000s)

1

2

3

4

5

6

t'7

l1

19

23

18

16

20

18

22

20

15

22

(see Problem 5-21)' Published bY Prentice Hall'

fr .: r. ;;:." i.\"r,. arz'a 3 -Y ear inov r 1: i'.,Tl::;

:;:;; :,Tt?; ;i;;;;.. i b( d e rn an d 1" i.'::'ll:',"' oivcni6 Problem 5-17' As\[mc

that last Tl::^t ; t".";""t 1 is -5,000 bags to begin

the pro-

.'r;;i;1"" Prefer to 1" .'n: -:-11:Y::1cedure' YYlrLrru 'luu " , *"ight"tl average model smoothing model or the

.,,'r"i r*A i,r Pt'oblem 5- l7'l Explain your answel' '

,150

495

518

563

584

?

MONT}I

ld have a wcight of 3'-*.".u.Y of each of these :"h"1:

f;;;;t *ign, n' Lowenthal consider

The sales manager had predicted' before lhe busincss

-,*;, ;;il"i r"' saies would. l" o]:":': ::l:,1;'stafl'eo' Lrtar Jw@ ' " "* i smoothing with a weight

tioners. Using exponential smootmng *t^".'i.::;

;;;^; o.io,"o*aop totecasts for years 2 ttuough 6'

-0:6 uo9 0'9' devetoP

forecasts for the sales of CooI-Man air condidoners

euantitative Anatysis ror Manasement, Twelfth Edition' bv Barry Render'

Ralph M' stair' Michael E' Hanna' 'tt]Jffit%!8i; ilB:':;:Hffi::i'';;: ;;'

ionclitioners have grown

steadilY during the Past 5 Years:

have a weight

a weight of 2. and

peri ods.

'7

8

,/\ ,/ tl

12

{orccast lbrweck I of 17'000

smoothing t0 computc 12.Useu:()'2'