Quantitative Methods

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A

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C

D

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The coelficient ol'correlation compuled was 0.68.

(a) If Thomas Williams returns from a 300-miie trip that took hirn out of town for 5 days, what is the expected amount that he should clairn as expenses'/

(b) Williams submitted a rcimburscnrcrll rcqucst Iilr $685; what should the accountant do?

(c) Comment on the validity of this model. Should any other variables be included? Which ones? Why?

Thirteen students cntered the undergraduate business program at Rollins College 2 years ago. The following table indicafes what thcir grade-point averages (GPAs) were atier being in the program fbr 2 years and what each student scorcd on the SAT exam (maximurn 2400) when he or she was in high school. ls there a meanin-gful relationship between gradcs and SAT sceires'l Il'a sludcnt seorcs a I 200 on the SAT. what do you think his or her GPA will he? What about a student who scores 2400?

126-7 2.90 IrI 2.93 1755 3.00 2010 3.45 182.1 3.66 1170 2.88 1245 2.1-s

H 144-3 2.53 I 2181 3.22 J 1503 1.99 K 18.1() 2.15 L 2127 .1.90 N..r i098 1.60

and subway ridership in Washington, D.C., dur- ing the summer months is believed to be heavily tied to the number of tourists visitin-s the city. During the past 12 ycars. the lbllowing dal:r have bcen oblained:

DISCUSSTON QUESTTONS AND PROBLEMS 143

(d) If there are no tourists at all, explain the pre- dicted ridcrship.

4-20 Use computer software to develop a regression model for the data in Problem 4-19. Explain what this output indicates about tho uscfulness ofthis model.

4-21 The fbitowing data give the starting salary for stu- dents who rccently graduated fiom a local university and acceptcdjobs soon aftcr-{raduation. The stating salary, grade-point average (GPA), and ma.jor (busi- ness or other) are provided.

SALARY "$29.s00 $46,000 $39,800 $36,500 GPA -3.I 3.5 3.8 2.9 Major Other -Business Business Other SALARY S42,OOO CPA 3.4 Major Business

$31,500 $36,200 2.t 2.5

Other Busincss

STT]DENT SAT SCORE GPA STUDENT SATSCORE CPA

(a) Llsing a computer, develop a regression model that could be used to predict starting salary based on GPA and major.

(b) LJse this model to predict the starting salary lbr a husincss maior with a GPA o1'3.0.

(c) What does the model say about the starting sal- ary fbr a business major compared to a nonbusi- ness major'?

(d) Do you believe this model is useful in predicting the stating salary? Justily your answer, using in- fbrmation provided in the computer output.

1-?2 The [ollowing data givc thc selling pricc. squlrr- footage, number of bedrooms. and age of houses that have sold in a neighborhood in the past 6 rnonths. Develop three reglession rnodels to pre- dict thc sclling price bascd upon cach of thc othcr facbrs individually. Which of these is best?

NUMBERO}' TOURISTS (1,000,000s)

RIDERSHIP (100,000s)

SELLING SQUARE PRICE ($) FOOTAGE

AGE BEDROOMS (rEARS)

YEAR

I

2

3

4

5

6

'7

8

9

l0

11

t2

1

2

6

4

1r+

l5

16

t2

t4

20

l5

7

l5

t0

l3

15

25

21

24

20

21

44

34

17

1,670

1,339

1,1 t2

l,B4t)

2.300

t.l)+

2,31 r

) 776

2,500

2,500

) 41q

2,400

30

2-s

30

40

l8

30

l9

1

t0

I

3

3

I

0

2

10

3

84,000

79,000

91,500

l 20.000

I 27.500

I 32,500

l4-s,00i)

164,000

I.55,000

t 6ti,000

l 72,500

174,000

175,000

1 77.500

1 84,000

I9-s,500

r 95,000

2

2

3

3

3

3

3

3

1

3

'1

3

f

l rlJ I

2,500 3 4,062 1 2,854 3

(a) Plot these data and dcterrnine whether a linear model is rcasonable.

(b) Develop a regression model. (c,) What is expected ridership if 10 million tourists

visit the city? Quantitative Analysis for Management, Twelfth Edition, by Barry Render, Ralph M- Stair, Copyright O 201 5 by Pearson Education, !nc.

E. Hanna, and Trevor S. Hale. Published by Prentice Hall.