CPU data frame: CpuTime CardsIn LinesOut Steps MountedDevices 1 0.4190 297 11714 15 0 2 0.4678 387 13901 15 0 3 0.0543 349 791 3 3 4 0.0590 468 965 3 3 5 0.0360 12 254 3 3 6 0.0676 713 1411 3 3 7 0.0893 18 266 2 1 8 0.0386 11 120 1 1 9 0.0988 18 245 2 1 10 0.0260 11 102 1 1 11 0.0410 18 307 2 1 12 0.0196 12 143 1 1 13 0.1653 17 4299 5 2 14 0.1421 17 925 2 1 15 0.0620 17 3076 5 2 16 0.0560 17 914 2 1 17 0.1405 17 3946 5 2 18 0.0316 14 429 1 2 19 0.2260 91 4781 13 3 20 0.0417 14 1329 1 2 21 0.4217 238 14872 13 3 22 0.0278 14 249 1 2 23 0.1873 100 4006 13 3 24 0.2035 65 1234 6 8 25 0.0410 17 152 1 1 26 0.2042 94 1366 8 8 27 0.2172 65 1228 6 8 28 0.2005 65 1231 6 8 29 0.2622 51 4098 13 3 30 0.0537 14 1869 1 2 31 0.3073 200 6691 13 3 32 0.0430 14 1102 1 2 33 0.2483 88 5028 13 3 34 0.0718 14 2716 1 2 35 0.4587 273 12016 13 3 36 0.2477 50 3934 13 3 37 0.2990 245 7214 13 3 38 0.1927 65 1230 6 8 Full regression model: Call: lm(formula = CpuTime ~ CardsIn + LinesOut + Steps + MountedDevices, data = cpu) Residuals: Min 1Q Median 3Q Max -0.077464 -0.017653 -0.000394 0.015306 0.089127 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 2.700e-03 1.093e-02 0.247 0.806368 CardsIn -2.884e-05 4.029e-05 -0.716 0.479161 LinesOut 2.165e-05 2.839e-06 7.627 8.86e-09 *** Steps 9.182e-03 2.113e-03 4.345 0.000125 *** MountedDevices 1.237e-02 2.916e-03 4.242 0.000168 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 0.03484 on 33 degrees of freedom Multiple R-squared: 0.9372, Adjusted R-squared: 0.9296 F-statistic: 123.1 on 4 and 33 DF, p-value: < 2.2e-16 Regression model with CardsIn removed: Call: lm(formula = CpuTime ~ LinesOut + Steps + MountedDevices, data = cpu) Residuals: Min 1Q Median 3Q Max -0.074914 -0.020733 0.001676 0.016939 0.090459 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 1.466e-03 1.071e-02 0.137 0.891959 LinesOut 2.109e-05 2.709e-06 7.786 4.64e-09 *** Steps 9.241e-03 2.096e-03 4.408 9.90e-05 *** MountedDevices 1.218e-02 2.883e-03 4.225 0.000169 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 0.03459 on 34 degrees of freedom Multiple R-squared: 0.9362, Adjusted R-squared: 0.9306 F-statistic: 166.4 on 3 and 34 DF, p-value: < 2.2e-16 Regression model with CardsIn removed, standardized coeffcients: Call: lm(formula = scale(CpuTime) ~ scale(LinesOut) + scale(Steps) + scale(MountedDevices), data = cpu) Residuals: Min 1Q Median 3Q Max -0.57062 -0.15792 0.01276 0.12902 0.68903 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 5.171e-17 4.274e-02 0.000 1.000000 scale(LinesOut) 6.363e-01 8.172e-02 7.786 4.64e-09 *** scale(Steps) 3.615e-01 8.201e-02 4.408 9.90e-05 *** scale(MountedDevices) 2.082e-01 4.929e-02 4.225 0.000169 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 0.2634 on 34 degrees of freedom Multiple R-squared: 0.9362, Adjusted R-squared: 0.9306 F-statistic: 166.4 on 3 and 34 DF, p-value: < 2.2e-16