Confidence intervals interpretation help
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Hi all! I have the following code:
Linear regression model:
y ~ 1 + x1
Estimated Coefficients:
Estimate SE tStat pValue
________ _______ _______ __________
(Intercept) 10.035 0.55554 18.064 2.2246e-08
x1 -2.3583 0.18476 -12.765 4.542e-07
Number of observations: 11, Error degrees of freedom: 9
Root Mean Squared Error: 0.315
R-squared: 0.948, Adjusted R-Squared 0.942
F-statistic vs. constant model: 163, p-value = 4.54e-07
>> coefCI(ci)
ans =
8.7784 11.2919
-2.7763 -1.9404
An I am having trouble interpreting the confidence intervals, can someone help me out please? Thanks a lot!
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Star Strider
2018-1-31
The confidence intervals correspond to:
(Intercept) 10.035 8.7784 11.2919
x1 -2.3583 -2.7763 -1.9404
The hypothesis the parameter confidence intervals test is that the parameters are not significantly different from zero. If they are (the confidence intervals have opposite signs) the parameter is not needed in the model. Here they both have the same signs for each parameter, so the parameters are each significantly different from zero, and both parameters are necessary to explain the model.
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