MATH
simple linear regressio

# The regressions explain 81 and 75 of the variation

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The regressions explain 81% and 75% of the variation, respectively. Does ARGUS takes larger time per byte as well as a larger set up time per call than UNIX?

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14-31 ©2008 Raj Jain CSE567M Washington University in St. Louis Case Study 14.1 (Cont) Case Study 14.1 (Cont) ! Intervals for intercepts overlap while those of the slopes do not. Set up times are not significantly different in the two systems while the per byte times (slopes) are different.
14-32 ©2008 Raj Jain CSE567M Washington University in St. Louis Confidence Intervals for Predictions Confidence Intervals for Predictions ! This is only the mean value of the predicted response. Standard deviation of the mean of a future sample of m observations is: ! m =1 Standard deviation of a single future observation:

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14-33 ©2008 Raj Jain CSE567M Washington University in St. Louis CI for Predictions (Cont) CI for Predictions (Cont) ! m = Standard deviation of the mean of a large number of future observations at x p : ! 100(1- α )% confidence interval for the mean can be constructed using a t quantile read at n-2 degrees of freedom.
14-34 ©2008 Raj Jain CSE567M Washington University in St. Louis CI for Predictions (Cont) CI for Predictions (Cont) ! Goodness of the prediction decreases as we move away from the center.

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14-35 ©2008 Raj Jain CSE567M Washington University in St. Louis Example 14.5 Example 14.5 ! Using the disk I/O and CPU time data of Example 14.1, let us estimate the CPU time for a program with 100 disk I/O's. ! For a program with 100 disk I/O's, the mean CPU time is:
14-36 ©2008 Raj Jain CSE567M Washington University in St. Louis Example 14.5 (Cont) Example 14.5 (Cont) ! The standard deviation of the predicted mean of a large number of observations is: ! From Table A.4, the 0.95-quantile of the t-variate with 5 degrees of freedom is 2.015. 90% CI for the predicted mean

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14-37 ©2008 Raj Jain CSE567M Washington University in St. Louis Example 14.5 (Cont) Example 14.5 (Cont) ! CPU time of a single future program with 100 disk I/O's: ! 90% CI for a single prediction: