Source Model .007361756 .02417575 Residual Total 8_KO 8 SP500 _cons SS .031537506 df 1 .007361756 249 .000097091 250 MS Coef. Std. Err. .4753727 .0545926 .0006781 .0006219 .00012615 Number of obs F(1, 249) Prob > F R-squared Adj R-squared Root MSE t P>|t| 8.71 0.000 1.09 0.277 = .3678506 -.0005469 251 75.82 0.0000 0.2334 0.2304 .00985 [95% Conf. Interval] 5828949 .001903

Trigonometry (MindTap Course List)
8th Edition
ISBN:9781305652224
Author:Charles P. McKeague, Mark D. Turner
Publisher:Charles P. McKeague, Mark D. Turner
Chapter4: Graphing And Inverse Functions
Section: Chapter Questions
Problem 6GP: If your graphing calculator is capable of computing a least-squares sinusoidal regression model, use...
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Estimate the linear regression model 9ABC = a +ß × g_SP500 and report 95% confidence level
for ß coefficient.
Transcribed Image Text:Estimate the linear regression model 9ABC = a +ß × g_SP500 and report 95% confidence level for ß coefficient.
Source
Model
Residual
Total
g_KO
8 SP500
_cons
SS
.007361756
.02417575
.031537506
df
1
249
250
Coef. Std. Err.
.4753727 .0545926
.0006781
0006219
MS
.007361756
.000097091
.00012615
Number of obs
F(1, 249)
Prob > F
R-squared
Adj R-squared =
Root MSE
t P>|t|
8.71 0.000
1.09 0.277
=
.3678506
-.0005469
251
75.82
0.0000
0.2334
0.2304
.00985
[95% Conf. Interval]
.5828949
.001903
Transcribed Image Text:Source Model Residual Total g_KO 8 SP500 _cons SS .007361756 .02417575 .031537506 df 1 249 250 Coef. Std. Err. .4753727 .0545926 .0006781 0006219 MS .007361756 .000097091 .00012615 Number of obs F(1, 249) Prob > F R-squared Adj R-squared = Root MSE t P>|t| 8.71 0.000 1.09 0.277 = .3678506 -.0005469 251 75.82 0.0000 0.2334 0.2304 .00985 [95% Conf. Interval] .5828949 .001903
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