1 48.5 32.4 11,168 2 48.2 31.7 11,150 3 44.5 31.9 11,186 4 44.7 36.6 11,381 5 49
ID: 3158898 • Letter: 1
Question
1
48.5
32.4
11,168
2
48.2
31.7
11,150
3
44.5
31.9
11,186
4
44.7
36.6
11,381
5
49.3
36.7
11,679
6
49.3
38.7
12,081
7
46.1
39.5
12,222
8
46.2
41.2
12,463
9
47.7
43.3
12,622
10
48.3
39.4
12,269
11
47.0
40.1
12,354
12
47.9
42.1
13,063
13
47.8
45.2
13,326
(Two Stocks and DJIA) The closing stock prices for each of two stocks were recorded over a 13-month period. The closing prices for the Dow Jones Industrial Average (DJIA) index were also recorded over the same time period. Month Stock 1 Stock 2 DJIA1
48.5
32.4
11,168
2
48.2
31.7
11,150
3
44.5
31.9
11,186
4
44.7
36.6
11,381
5
49.3
36.7
11,679
6
49.3
38.7
12,081
7
46.1
39.5
12,222
8
46.2
41.2
12,463
9
47.7
43.3
12,622
10
48.3
39.4
12,269
11
47.0
40.1
12,354
12
47.9
42.1
13,063
13
47.8
45.2
13,326
Use the Excel data (Two Stocks and DJIA Model 1 Data) to develop a regression model (model 1) to predict the price of stock 1 based on DJIA. Let Y = price of stock 1 and X = DJIA.
Use the Excel data (Two Stocks and DJIA Model 2 Data) to develop a regression model (model 2) to predict the price of stock 2 based on DJIA. Let Y = price of stock 2 and X = DJIA.
(Two Stocks and DJIA) Use model 2 to predict the price of stock 2.
(a) The intercept (b0) is ___. [Answer format: two decimal places]
(b) The slope coefficient (b1) is ___. [Answer format: four decimal places]
(c) If the next month's DJIA is 13500, the predicted price of stock 2 is $___. (Hint: To avoid rounding errors, use the exact numbers in (a) and (b).) [Answer format: two decimal places]
Write your answer(s) as -12.34, 5.6789, 23.45
Explanation / Answer
Use the Excel data (Two Stocks and DJIA Model 1 Data) to develop a regression model (model 1) to predict the price of stock 1 based on DJIA. Let Y = price of stock 1 and X = DJIA.
The regression model to predict the price of stock 1 based on DJIA is given as below:
SUMMARY OUTPUT
Regression Statistics
Multiple R
0.187627675
R Square
0.035204145
Adjusted R Square
-0.05250457
Standard Error
1.603963525
Observations
13
ANOVA
df
SS
MS
F
Significance F
Regression
1
1.032618801
1.032619
0.401376
0.539329066
Residual
11
28.29968889
2.572699
Total
12
29.33230769
Coefficients
Standard Error
t Stat
P-value
Lower 95%
Upper 95%
Intercept
42.43247825
7.768625337
5.462032
0.000197
25.33384918
59.53110732
DJIA
0.000406958
0.000642354
0.633542
0.539329
-0.001006853
0.001820769
The regression equation is given as below:
Stock 1 = 42.4325 + 0.0004*DJIA
Use the Excel data (Two Stocks and DJIA Model 2 Data) to develop a regression model (model 2) to predict the price of stock 2 based on DJIA. Let Y = price of stock 2 and X = DJIA.
The regression model to predict the price of stock 2 based on DJIA is given as below:
SUMMARY OUTPUT
Regression Statistics
Multiple R
0.961226308
R Square
0.923956015
Adjusted R Square
0.917042925
Standard Error
1.250572788
Observations
13
ANOVA
df
SS
MS
F
Significance F
Regression
1
209.024437
209.024437
133.6531238
1.70492E-07
Residual
11
17.20325527
1.563932298
Total
12
226.2276923
Coefficients
Standard Error
t Stat
P-value
Lower 95%
Upper 95%
Intercept
-31.54007643
6.057015195
-5.20719784
0.000291216
-44.87147698
-18.20867588
DJIA
0.005789996
0.000500828
11.56084443
1.70492E-07
0.004687681
0.006892312
The regression equation is given as below:
Stock 2 = -31.54 + 0.0058*DJIA
(a) The intercept (b0) is ___. [Answer format: two decimal places]
The intercept is given as -31.54.
(b) The slope coefficient (b1) is ___. [Answer format: four decimal places]
The slope coefficient is given as 0.0058.
(c) If the next month's DJIA is 13500, the predicted price of stock 2 is $___.
The regression equation is given as
Stock 2 = -31.54 + 0.0058*DJIA
Stock 2 = -31.54 + 0.0058*13500
Stock 2 = $46.76
Predicted price of stock 2 is $46.76.
SUMMARY OUTPUT
Regression Statistics
Multiple R
0.187627675
R Square
0.035204145
Adjusted R Square
-0.05250457
Standard Error
1.603963525
Observations
13
ANOVA
df
SS
MS
F
Significance F
Regression
1
1.032618801
1.032619
0.401376
0.539329066
Residual
11
28.29968889
2.572699
Total
12
29.33230769
Coefficients
Standard Error
t Stat
P-value
Lower 95%
Upper 95%
Intercept
42.43247825
7.768625337
5.462032
0.000197
25.33384918
59.53110732
DJIA
0.000406958
0.000642354
0.633542
0.539329
-0.001006853
0.001820769
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