Quickstart

val sample = doubleArrayOf(2.0, 4.0, 4.0, 4.0, 5.0, 5.0, 7.0, 9.0)

val stats = sample.describe()
stats.mean              // 5.0
stats.median            // 4.5
stats.standardDeviation // 2.1380
stats.skewness          // 0.6563
stats.interquartileRange // 1.5

val normality = shapiroWilkTest(sample)
normality.statistic          // W statistic
normality.pValue             // > 0.05 → no evidence against normality
normality.isSignificant()    // false

val normal = NormalDistribution(mu = stats.mean, sigma = stats.standardDeviation)
normal.cdf(6.0)          // probability that X ≤ 6.0
normal.quantile(0.95)    // value below which 95% of the distribution falls

val result = tTest(sample, mu = 5.0)
result.statistic         // 0.0
result.pValue            // 1.0
result.isSignificant()   // false — cannot reject H₀: μ = 5.0
result.confidenceInterval // (3.21, 6.79)

val x = doubleArrayOf(1.0, 2.0, 3.0, 4.0, 5.0)
val y = doubleArrayOf(2.1, 3.9, 6.2, 7.8, 10.1)

val r = pearsonCorrelation(x, y)
r.coefficient            // 0.9987
r.pValue                 // 0.0001

val model = simpleLinearRegression(x, y)
model.slope              // 1.99
model.rSquared           // 0.9973
model.predict(6.0)       // 11.99