Statistics
Standard statistics utilities.
Standard statistics utilities.
Note: significance level alpha is equal to 1 - confidenceLevel. If you want to
be sure that 2 sets of measurements do not differ with 90 percent probability, then
the significance level alpha should be set to 0.1.
In this example, the confidence level is 0.9, and the significance level is 0.1.
Type members
Classlikes
ANOVA separates the total variation in a set of measurements into a component due to random fluctuations in the measurements and a component due to the actual differences among the alternatives.
ANOVA separates the total variation in a set of measurements into a component due to random fluctuations in the measurements and a component due to the actual differences among the alternatives.
If the variation between the alternatives is larger than the variation within each alternative, then it can be concluded that there is a statistically significant difference between the alternatives.
For more information see: Andy Georges, Dries Buytaert, Lieven Eeckhout - Statistically Rigorous Java Performance Evaluation
Compares the coefficient of variance to some threshold value.
Compares the coefficient of variance to some threshold value.
This heuristic can be used to detect if the measurement has stabilized.
Compares two alternative sets of measurements given a significance level alpha.
Compares two alternative sets of measurements given a significance level alpha.
- Value Params
- strict
if
true, the confidence interval test is strict - the confidence interval overlap of the alternatives will not be additionally compared
- Returns
returns
trueif there is no statistical difference for s.l.alpha
Computes the confidence interval of the two alternatives.
Passes if the confidence intervals overlap at the given significance level alpha.
Computes the confidence interval of the two alternatives.
Passes if the confidence intervals overlap at the given significance level alpha.
Applies relative noise before doing the actual overlap test - the relative noise may increase the confidence interval further, but it will not shrink it.
Value members
Concrete methods
Computes sum-of-squares due to differences between alternatives.
Computes sum-of-squares due to differences between alternatives.
Computes sum-of-squares due to errors in measurements.
Computes sum-of-squares due to errors in measurements.
Let Y = (Y_1, ..., Y_n) data resulting from a parametric law F of scalar parameter θ. A confidence interval (B_i, B_s) is a statistic in the form of an interval containing θ with a specified probability.
Let Y = (Y_1, ..., Y_n) data resulting from a parametric law F of scalar parameter θ. A confidence interval (B_i, B_s) is a statistic in the form of an interval containing θ with a specified probability.
Computes the mean of the sequence of measurements.
Computes the mean of the sequence of measurements.