The regression equation is Duration = - 2.45 + 0.0767 Time SE Coef 0.2556 Predictor Coef P Constant -2.4454 -9.57 0.000 Time 0.076739 0.003360 22.84 0.000 0.225947 R-Sq 95.8% %3D Analysis of Variance Source DF MS F P Regression 1 26.633 26.633 521.69 0.000 Residual Error 23 1.174 0.051 Total 24 27.807 The above regression results are from the duration of Old Faithful's eruptions as a function of the time since the last eruption.

MATLAB: An Introduction with Applications
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Author:Amos Gilat
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a. Can you construct a 95% confidence interval for the y intercept for the regression equation then justify the correlation between time and duration? 

b. Also, what are the chances of seeing a relationship between time and duration as strong or stronger than this, when in fact there was none?

The regression equation is
Duration
= - 2.45 + 0.0767 Time
Predictor
Coef
SE Coef
P
Constant
-2.4454
0.2556 -9.57
0.000
Time
0.076739 0.003360
22.84
0.000
S = 0.225947
R-Sq
95.8%
Analysis of Variance
Source
DF
SS
MS
F
P
Regression
1.
26.633
26.633 521.69
0.000
Residual Error 23
1.174
0.051
Total
24 27.807
The above regression results are from the duration of Old Faithful's eruptions as a function of the time
since the last eruption.
Transcribed Image Text:The regression equation is Duration = - 2.45 + 0.0767 Time Predictor Coef SE Coef P Constant -2.4454 0.2556 -9.57 0.000 Time 0.076739 0.003360 22.84 0.000 S = 0.225947 R-Sq 95.8% Analysis of Variance Source DF SS MS F P Regression 1. 26.633 26.633 521.69 0.000 Residual Error 23 1.174 0.051 Total 24 27.807 The above regression results are from the duration of Old Faithful's eruptions as a function of the time since the last eruption.
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