Quantitative Methods

l;J::::::.I'b,u " 4-9 J has developed the follow forecastin

mode

i:36+

K10 air oners

re ("F)

(a) Forecast the turc is 70'F.

(h) What is the (c) What is demand

$: a-lo rhe opera distribu feels that demand l'or a particular type ol -qu may be related to the number of YouTube

' a music video by the popular rock group Pumpkins during the preceding month. The

has collected the data shown in the follow-

YouThbe GUTIAR \aIEWS (l,fins) SALES

h these data to hether a iinear equa- mieht describe t relationship between the

onYouTube guitar sales. the equ presented in this chapter,

the ', SSE, and SSR. Find the least-

for K10 when the

a tcmperaturcr of 80oF? a tcmperature of 90'F?

30

40

70

60

80

-50

4-t6 Caples, a real estate appraiser in Charles. to help

appr residential housing in t Charles area. The ,l was developed recently sold homes in a The price (11 of the house is on the footage (X) ol'the house. The 1S

Y 33,478 62.lX

The coellcient ol lbr the model is 0.63.

squal'cs (c) Using t

Using a

line for these data. regression equation, predict guitar

sales i yere 40,000 views last month.

nr 4- 10, tcst to st:e il' thcrc is t relationship hetu'een sales

(b) A house with 1, feet recently sold lbr.$165.000. E: model prcdictcd.

this is not what thc

(c) If you were goin ipie regression tcr develop an model, other quantita- tive variables mi ht be inc in the model?

(a) Use the model to house that is 1.860

(d) What is the model?

ct the selling price of a feet.

YouTube views 0.05 level o[ sienilrcance. icient of de ation for this

andAppendix D.

[-lsing computer software) nd the least-scluarL's re- 4-11

grcssion line lbr the data in 4-10. Based on the F test, is there a statist significant relation- hish travel vo

ship between the demand for gu and the number ness trrps. ThL' vouchers sn

relating ex travel cost (l) to numbr:r of days on the road (X1 ) and distauce traveled (X2) in miles:

i : $90.00 + $48.50x1 + $0.40x2

Quantitative Analysis fo{ Management,Iwelfth Ediuon, by Ba.ry Render, Ralph M. Stair, Michael E. Hanna, and Trevor S. Hale. Published by Prentice Hall. Copyright O 2015 by Pearson Education, Inc.

lbr the same students. Somc of these grades have bccn sarnpled and arc as lbllows:

I st test grade

Final average

98 11 88 93 '78 8,1

80 96 6l 73 8,+ 64

(a) Develop a regression model that couid be used to predict the frnal average in the course based on the first test grade.

(b) Predict the final average of a student who made an 83 on the flrst test.

(c) Give the values of r and 12 for this model. Inter-

-/-----\ prct the value ol 12 in thc contcxt ol this problcm. / 4-14 ,ilsinu rhe data in Problern ,{-13, test to see if there# is a statistieally significant relationship between the

-{radc on the first tcst and the ilnal nvcragc at the 0.05 level of significance. Use the lormulas in this e hrpter rnd Appcndir D.

[ +-l 5 lsing computcr software, lincl thc lcast-squarcs regres- sion line [ot the data in Problem 4-13. Bascd on the F test, is there a stalistically signilicant relationship between

*re first test grade and the final

Accountants at thefirm Walker and Walfur bclieved that several traveflng executives submit \usually

ii-a rnanagement science class have just re- ceived their grades on the lirst test. The instructor has provided infbrmation about the frrst tcst grades in some previous classes as well as the final average

may he solved with QM for Windowsl means tlre problem nray be soived rvith Ercel QM: anci rnealls the problern nay be solved rvith QIvl tbr Windorvs and/or F,xcel QM

whcre

Y: Xr :

rcgrcssion cquation

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when they return