ANOVA
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                      Df  Sum Sq Mean Sq   F value    Pr(>F)    
comm.strat             3  0.0168  0.0056    0.4551 0.7137186    
migr.freq              1  0.0593  0.0593    4.8180 0.0284078 *  
max.cpu                1  0.5297  0.5297   43.0242  8.91e-11 ***
instance               1 14.8789 14.8789 1208.4193 < 2.2e-16 ***
comm.strat:migr.freq   3  0.2514  0.0838    6.8057 0.0001536 ***
comm.strat:max.cpu     3  0.0219  0.0073    0.5929 0.6197214    
comm.strat:instance    3  0.0109  0.0036    0.2963 0.8280872    
migr.freq:max.cpu      1  0.0077  0.0077    0.6236 0.4299149    
migr.freq:instance     1  0.0503  0.0503    4.0880 0.0434721 *  
max.cpu:instance       1  0.1053  0.1053    8.5512 0.0035357 ** 
Residuals            941 11.5862  0.0123                        
---
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 0.4017   0.3904 0.4131
8 == 0 0.3547   0.3434 0.3661

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   
fnl4461 == 0 0.2537   0.2424 0.2651
rl5915 == 0  0.5027   0.4914 0.5141

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 0.3861   0.3747 0.3974
s == 0 0.3704   0.3590 0.3817

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 0.3740   0.3561 0.3918
HC == 0 0.3847   0.3668 0.4025
R == 0  0.3751   0.3572 0.3930
RW == 0 0.3791   0.3613 0.3970

95% family-wise confidence level
 

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