Below is shown a set of 25 data pairs. A common cross-validation method uses the

Question

Below is shown a set of 25 data pairs. A common cross-validation method uses the so-called "leave-one-out" (LOO) approach in which each point is eliminated and the model developed from the remaining n-1-24 points is used to estimate the missing value. In this way, n quasi-independent estimates are determined from the data set of n data points. For each of the four data sets, make a list of the 25 different a's and k's and be prepared to complete the following table. Indicate units if the parameter has units. USE THE QUARTILE RULES FROM THE FIRST FEW WEEKS OF CLASS. Minimum! Maximum, Mean Minimum Maximum Median Q Median Q' 3 Slope "m Intercept "b "Quasi-independent Residual" (I'll clarify this during class) 2.293 0.551 8.652 6.162 6.107 8.152 5.604 0.109 0.552 0.103 5.706 4.29879 1.083 2.1523.071 2.779 2.653 3.252 3.680 2.822 0.361 6.172 6.734 8.314 7669 5.475 5.709 9.365 8.3949.67812.723 948512.493 2.232 2.802 3.185 1.383 8977 10.113 .6 1.366 0.078 5567 2.947 4.179

Explanation / Answer

SUMMARY OUTPUT Regression Statistics Multiple R 0.862547 R Square 0.743988 Adjusted R Square 0.732857 Standard Error 1.877852 Observations 25 ANOVA df SS MS F Significance F Regression 1 235.6981 235.6981 66.83952 2.95E-08 Residual 23 81.10554 3.526328 Total 24 316.8036 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept -0.94255 0.763852 -1.23395 0.229682 -2.5227 0.637593 -2.5227 0.637593 X 1.05005 0.128438 8.175544 2.95E-08 0.784356 1.315744 0.784356 1.315744

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