Quantitative Methods
chxarily
img_20160313_0003.pdf
: q.ur.hr,"r, L/*3o DtscusstoN QUESIoNS AND PROBLEMS 145
CATEGORY
Puhhc
Private
Pri\ ato
Pril atcr
Private
Privirte
Prlvatd
Private
20.200
10,.100
4t, I (X)
100
100
-14
cosr ($) MI'DIAN SAT TEAM OBPAVGERA r 620
1 610
I tt.l0
19ti0
1 930
2 t30
2010
1 590
1720
t]10
B-5
68 8\ 72' 89
4.02
4.78
3.75
4
4.1',7
3.85
3.48
3.16
3.19
f .99
+. o+
126
676
'76'7
101
0.25.5
0.251
0.268
0.265
0.211
0.260
0.265
0.238
0.23,+
0.3 rn
0.324
0.335
0.317
0.332
0.325
0.337
0.31 0
0.296
0.317
Baltimore 0rioles
Boston Rerl Sor
Chicago White Sox
Cleveland Indians
Detoit Tigers
Kansas City Royals
Los Angeies Angels
IV{innesota Twins
New York Yankecs
Oakland Athletics
Seattle Mariners
Tampa Ray Rays
Teras Rangers
Toronto Blue Jays
3.90 7l.2 0.247 0.31 1 4.10 134 0.260 0..i 15
93
69
12" 1 00
3 r .{i00
66
94
't5
90
93
't3
619
691
32" I 00 't
S: +:! h ZtltZ. the total payroli for the New l'ork Yankees was almost $200 million, whilc the total payroll fbr the Oakland Athletics (a team known fbr using base- ball analytics or sabermetrics) was about $55 million, lc:ss than one-third o{ the Yankees payroll. In thc fol- lowing table. you q,ill see the payrolls (in millions) and thc total rumb.:r ol- victories I'or the baseball tcams in thc American l-eague in the 20l2 soason. Devclop a regression nrodel to predict the total rtum-
ber of victories based on tht: payroll. Use the model to predict the number of victones tor a team with a pay- roll oi ti79 million. Based on the results of the com- puter output, discuss the relationship betwecn payroll and victories.
(a) Dc-vclop a rcgrcssion modcl that could bc ttscd to predict the nunrber of based on the ERA.
ii08 0,273 0.33:t '716 0.245 0.309
(c)
(d)
(b) Develop a r prcdict the scored.
Deveiop a predict the ting aver Develt.rp a
1
2
3
4
5
6
7
8
9
it)
11,
that could be used to ies based on the runs
that could be used to ies based on the bat-
could be used to
TEAM PAYROLL
($MTLLIONS) NUMBEROF VICTORIES
prcdict number of victories based on the on- base
(e) of the four models is bener tbr pre<licting the r of victories?
(t) Find the best multiple regression rnodel to pre- dict the nurnber of wins. Use any combination of the variables to tind the best nrodel.
4-32 The closing stock price for each o1' two stocks
(DJIA) was also over this same time
MONTH D.IIA
Baltimore Orioles
Boston Red Sox
Chicago White Sox
Cleveiand Inciians
Detroit Tigers
Kansas City Royals
Los Angele s Angels
Minncsota Ts,ins
Ncrv York Yankees
0akland Athletics
Seattle Mariners
Tampa Bay Rays
Texas Rangers
Toronto Blue Jays
81 .4
113.2
96.9
78.1
132.3
60.9
154"5
94.1
198.0
55..1
82.0
61.2
120.5
75.5
93
(t9
85
68
ri8
72
89
66
95
94
75
90
9?
73
.7
.-1
.-1
.1-ll Thc number of t,ictories (W), earned flrn average (ERA), runs scored (R), batting (AVG), and on-base ntage ( each team in the
scason are providcd in the following t ERA is one mcasure of the effective tching staff, and a lower
statistics are measures oI effecti hisher numbers arc number is
11,168
11.150
11,1ti6
1i,381
11,679
2.463
1 t,6)1
12.26t)
I2..15.1
13.063
48.3
17.0
17.9
47.8
32.4
3t.'1
3 r.9
36.6
-tt./
3U.7
39.5
/1 f
4-3.3
39.4
.10.1
12.1
45.2 each of these.
Quantitative Analysis for Managemerrt, Twelfth Edition, by Barry Render, Ralph M. Stair, Michael E. Hanna, and Trevor S. Hale. Published by Prentice Hall.
Copyright @ 201 5 by Pearson Education, lnc.
was recordctl ovcr a f 2-month period. The cl,rs- ing plicc for the D{w Jones industrial Avcrage
r:iod. These
American .in ihc
