CrucibleBench.Stats (CrucibleBench v0.3.2)
View SourceCore statistical functions and utilities.
Provides basic statistical calculations used throughout the framework.
Summary
Functions
Calculate correlation coefficient between two variables.
Calculate kurtosis of a distribution.
Calculate mean (average) of a list of numbers.
Calculate median of a list of numbers.
Calculate quantile at given probability.
Rank values in ascending order, handling ties by averaging.
Calculate standard error of the mean.
Calculate skewness of a distribution.
Calculate standard deviation of a list of numbers.
Calculate variance of a list of numbers.
Calculate z-score for each value in a list.
Functions
Calculate correlation coefficient between two variables.
Returns Pearson correlation coefficient (-1 to 1).
Examples
iex> x = [1, 2, 3, 4, 5]
iex> y = [2, 4, 6, 8, 10]
iex> CrucibleBench.Stats.correlation(x, y)
1.0Calculate kurtosis of a distribution.
Excess kurtosis > 0 means heavy tails (leptokurtic). Excess kurtosis < 0 means light tails (platykurtic).
Calculate mean (average) of a list of numbers.
Examples
iex> CrucibleBench.Stats.mean([1, 2, 3, 4, 5])
3.0Calculate median of a list of numbers.
Examples
iex> CrucibleBench.Stats.median([1, 2, 3, 4, 5])
3.0
iex> CrucibleBench.Stats.median([1, 2, 3, 4])
2.5Calculate quantile at given probability.
Examples
iex> CrucibleBench.Stats.quantile([1, 2, 3, 4, 5], 0.5)
3.0Rank values in ascending order, handling ties by averaging.
Examples
iex> CrucibleBench.Stats.rank([5, 2, 8, 2, 9])
[3.0, 1.5, 4.0, 1.5, 5.0]Calculate standard error of the mean.
Examples
iex> CrucibleBench.Stats.sem([1, 2, 3, 4, 5])
0.7071067811865476Calculate skewness of a distribution.
Positive skew means right tail is longer. Negative skew means left tail is longer.
Calculate standard deviation of a list of numbers.
Examples
iex> CrucibleBench.Stats.stdev([1, 2, 3, 4, 5])
1.5811388300841898Calculate variance of a list of numbers.
Options
:sample- If true (default), uses n-1 denominator (sample variance):population- If true, uses n denominator (population variance)
Examples
iex> CrucibleBench.Stats.variance([1, 2, 3, 4, 5])
2.5Calculate z-score for each value in a list.
Examples
iex> CrucibleBench.Stats.z_scores([1, 2, 3, 4, 5])
[-1.2649110640673518, -0.6324555320336759, 0.0, 0.6324555320336759, 1.2649110640673518]