A financial analyst engaged in business valuation obtained financial data on 71
ID: 3225984 • Letter: A
Question
A financial analyst engaged in business valuation obtained financial data on 71 drug companies. Let Y correspond to the price-to-book value ratio, X1 correspond to the return on equity, and X2 correspond to the growth percentage. Use the accompanying data to complete parts a. through e. below.
Price/Book Value Ratio
Return on Equity
Growth%
1.523
13.058
6.461
8.326
11.796
135.702
2.087
12.358
0.061
6.583
25.212
14.203
1.349
8.882
22.808
3.294
38.032
19.079
2.401
25.659
24.558
5.183
19.767
11.704
2.403
22.751
49.942
7.763
69.772
36.631
0.432
3.853
41.165
2.407
9.151
28.934
7.636
29.117
52.129
5.063
17.814
25.127
2.189
29.252
23.791
4.717
31.414
9.622
2.109
14.746
18.566
3.979
11.954
39.133
1.926
14.261
39.371
1.432
14.176
27.133
2.005
14.937
13.243
4.956
20.703
17.191
2.335
14.817
15.935
1.995
5.587
16.779
2.833
11.173
8.347
1.735
16.261
18.249
5.527
23.897
16.716
4.582
14.801
46.615
2.575
6.163
34.102
1.633
19.102
8.556
8.361
39.011
15.005
2.225
15.264
25.226
2.893
19.741
0.384
7.476
18.314
3.272
3.349
20.757
9.453
2.719
34.738
7.143
2.408
15.399
9.482
1.184
10.376
4.789
2.969
23.481
4.138
10.145
91.588
13.368
2.054
1.532
15.826
1.513
9.456
5.648
2.005
19.448
0.049
7.099
4.903
102.808
1.327
42.815
1.611
5.669
90.909
74.083
6.454
19.336
9.059
2.572
27.357
34.524
3.394
13.002
12.097
6.998
24.509
11.572
13.574
81.916
24.522
4.094
1.378
20.242
7.093
3.552
22.303
6.072
31.479
49.911
1.009
5.023
13.167
9.346
47.896
61.131
1.303
13.313
10.759
0.996
36.033
8.989
3.882
28.765
71.115
3.533
18.011
51.913
2.239
13.949
16.956
10.169
132.958
171.256
4.211
21.881
8.481
8.449
11.265
247.822
2.036
17.356
10.745
3.991
19.449
6.327
2.327
8.619
24.449
2.884
18.678
14.341
4.572
21.705
5.784
5.041
49.576
31.498
2.113
19.255
3.894
a. Develop a regression model to predict price-to-book-value ratio based on return on equity.
Yi=____ + ____X1i
(Round to four decimal places as needed.)
b. Develop a regression model to predict price-to-book-value ratio based on growth.
Yi =____ + ____X2i
(Round to four decimal places as needed.)
c. Develop a regression model to predict price-to-book-value ratio based on return on equity and growth.
Yi =____ + ____X1i + ____X2i
(Round to four decimal places as needed.)
d. Compute and interpret the adjusted r2 for each of the three models.
Start with the part (a) model.
The adjusted r2 shows that ___% of the variation in ________ is explained by ______ _____ correcting for the number of independent variables in the model.
(Round to one decimal place as needed.)
Compute and interpret the adjusted r2 for the part (b) model.
The adjusted r2 shows that ___% of the variation in ____ is explained by ____ ____ correcting for the number of independent variables in the model.
(Round to one decimal place as needed.)
Compute and interpret the adjusted r2 for the part (c) model.
The adjusted r2 shows that ____%of the variation in ____ ____ is explained by ____ ____ correcting for the number of independent variables in the model.
(Round to one decimal place as needed.)
e. Which of these three models do you think is the best predictor of price-to-book-value ratio?
The model from ___ is the best predictor of price-to-book-value ratio because it has the ____ value of ____.
Price/Book Value Ratio
Return on Equity
Growth%
1.523
13.058
6.461
8.326
11.796
135.702
2.087
12.358
0.061
6.583
25.212
14.203
1.349
8.882
22.808
3.294
38.032
19.079
2.401
25.659
24.558
5.183
19.767
11.704
2.403
22.751
49.942
7.763
69.772
36.631
0.432
3.853
41.165
2.407
9.151
28.934
7.636
29.117
52.129
5.063
17.814
25.127
2.189
29.252
23.791
4.717
31.414
9.622
2.109
14.746
18.566
3.979
11.954
39.133
1.926
14.261
39.371
1.432
14.176
27.133
2.005
14.937
13.243
4.956
20.703
17.191
2.335
14.817
15.935
1.995
5.587
16.779
2.833
11.173
8.347
1.735
16.261
18.249
5.527
23.897
16.716
4.582
14.801
46.615
2.575
6.163
34.102
1.633
19.102
8.556
8.361
39.011
15.005
2.225
15.264
25.226
2.893
19.741
0.384
7.476
18.314
3.272
3.349
20.757
9.453
2.719
34.738
7.143
2.408
15.399
9.482
1.184
10.376
4.789
2.969
23.481
4.138
10.145
91.588
13.368
2.054
1.532
15.826
1.513
9.456
5.648
2.005
19.448
0.049
7.099
4.903
102.808
1.327
42.815
1.611
5.669
90.909
74.083
6.454
19.336
9.059
2.572
27.357
34.524
3.394
13.002
12.097
6.998
24.509
11.572
13.574
81.916
24.522
4.094
1.378
20.242
7.093
3.552
22.303
6.072
31.479
49.911
1.009
5.023
13.167
9.346
47.896
61.131
1.303
13.313
10.759
0.996
36.033
8.989
3.882
28.765
71.115
3.533
18.011
51.913
2.239
13.949
16.956
10.169
132.958
171.256
4.211
21.881
8.481
8.449
11.265
247.822
2.036
17.356
10.745
3.991
19.449
6.327
2.327
8.619
24.449
2.884
18.678
14.341
4.572
21.705
5.784
5.041
49.576
31.498
2.113
19.255
3.894
Explanation / Answer
Y = price-to-book value ratio,
X1 = return on equity
X2 = Growth percentage
a. Develop a regression model to predict price-to-book-value ratio based on return on equity.
Yi= 2.31025 + 0.0704 X1i
b. Develop a regression model to predict price-to-book-value ratio based on growth.
Yi =3.1141 + 0.0309 X2i
c. Develop a regression model to predict price-to-book-value ratio based on return on equity and growth.
Yi = 1.9190 + 0.0604 X1i +0.0219 X2i
d.
d. Compute and interpret the adjusted r2 for each of the three models.
Start with the part (a) model.
The adjusted r2 shows that 33.43 % of the variation in Price/Book Value Ratio is explained by Return on equity correcting for the number of independent variables in the model.
Compute and interpret the adjusted r2 for the part (b) model.
The adjusted r2 shows that 19.2% of the variation in Price/Book Value Ratio is explained by Growth % correcting for the number of independent variables in the model.
Compute and interpret the adjusted r2 for the part (c) model.
The adjusted r2 shows that 42.19 % of the variation in Price/Book Value Ratio is explained by Return on equity and Growth % correcting for the number of independent variables in the model.
e. Which of these three models do you think is the best predictor of price-to-book-value ratio?
The model from part (c) is the best predictor of price-to-book-value ratio because it has the Highest value of R - square .
SUMMARY OUTPUT Regression Statistics Multiple R 0.586353406 R Square 0.343810317 Adjusted R Square 0.334300322 Standard Error 2.204283456 Observations 71 ANOVA df SS MS F Significance F Regression 1 175.6602 175.6602 36.15252 7.75E-08 Residual 69 335.2617 4.858866 Total 70 510.922 Coefficients Standard Error t Stat P-value Lower 95% Intercept 2.310252434 0.38519 5.997697 8.23E-08 1.54182 Return on Equity 0.070400095 0.011709 6.012697 7.75E-08 0.047042Related Questions
drjack9650@gmail.com
Navigate
Integrity-first tutoring: explanations and feedback only — we do not complete graded work. Learn more.