ANOVA
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                      Df  Sum Sq Mean Sq  F value    Pr(>F)    
comm.strat             3 0.05636 0.01879  25.4344 7.956e-16 ***
migr.freq              1 0.04357 0.04357  58.9901 3.967e-14 ***
max.cpu                1 0.04181 0.04181  56.6162 1.237e-13 ***
instance               1 0.34793 0.34793 471.0844 < 2.2e-16 ***
comm.strat:migr.freq   3 0.01738 0.00579   7.8439 3.574e-05 ***
comm.strat:max.cpu     3 0.00586 0.00195   2.6466  0.047896 *  
comm.strat:instance    3 0.00327 0.00109   1.4780  0.218992    
migr.freq:max.cpu      1 0.00003 0.00003   0.0419  0.837901    
migr.freq:instance     1 0.00016 0.00016   0.2227  0.637085    
max.cpu:instance       1 0.00583 0.00583   7.8891  0.005076 ** 
Residuals            941 0.69499 0.00074                       
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 
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	 Simultaneous Confidence Intervals for General Linear Hypotheses

Multiple Comparisons of Means: Mean Contrasts


Fit: aov(formula = best ~ (comm.strat + migr.freq + max.cpu + instance)^2, 
    data = BestDF)

Estimated Quantile = 2.24

Linear Hypotheses:
       Estimate lwr     upr    
4 == 0 0.04683  0.04405 0.04961
8 == 0 0.03363  0.03085 0.03641

95% family-wise confidence level
 

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	 Simultaneous Confidence Intervals for General Linear Hypotheses

Multiple Comparisons of Means: Mean Contrasts


Fit: aov(formula = best ~ (comm.strat + migr.freq + max.cpu + instance)^2, 
    data = BestDF)

Estimated Quantile = 2.24

Linear Hypotheses:
             Estimate lwr     upr    
u1060 == 0   0.02119  0.01841 0.02397
nrw1379 == 0 0.05927  0.05649 0.06204

95% family-wise confidence level
 

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	 Simultaneous Confidence Intervals for General Linear Hypotheses

Multiple Comparisons of Means: Mean Contrasts


Fit: aov(formula = best ~ (comm.strat + migr.freq + max.cpu + instance)^2, 
    data = BestDF)

Estimated Quantile = 2.24

Linear Hypotheses:
       Estimate lwr     upr    
d == 0 0.03349  0.03071 0.03627
s == 0 0.04696  0.04419 0.04974

95% family-wise confidence level
 

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	 Simultaneous Confidence Intervals for General Linear Hypotheses

Multiple Comparisons of Means: Mean Contrasts


Fit: aov(formula = best ~ (comm.strat + migr.freq + max.cpu + instance)^2, 
    data = BestDF)

Estimated Quantile = 2.4955

Linear Hypotheses:
        Estimate lwr     upr    
FC == 0 0.04590  0.04153 0.05028
HC == 0 0.04645  0.04208 0.05083
R == 0  0.04110  0.03672 0.04548
RW == 0 0.02746  0.02308 0.03184

95% family-wise confidence level
 

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