# TODO: Real
.mean: |T <: Float|(data: Iterable(T)) -> T
.fmean: (data: Iterable(Float), weights := Iterable(Float)) -> Float
.geometric_mean: (data: Iterable(Float)) -> Float
.harmonic_mean: (data: Iterable(Float), weights := Iterable(Float)) -> Float
.median: (data: Iterable(Float)) -> Float
.median_low: (data: Iterable(Float)) -> Float
.median_high: (data: Iterable(Float)) -> Float
.median_grouped: (data: Iterable(Float), interval: Float) -> Float
.mode: (data: Iterable(Float)) -> Float
.multimode: (data: Iterable(Float)) -> Iterable(Float)
.pstdev: (data: Iterable(Float), mu := Float) -> Float
.pvariance: (data: Iterable(Float), mu := Float) -> Float
.stdev: (data: Iterable(Float), xbar := Float) -> Float
.variance: (data: Iterable(Float), xbar := Float) -> Float
.quantiles: (data: Iterable(Float), n := Nat, method := Str) -> [Float; _]
.covariance: (x: Iterable(Float), y: Iterable(Float)) -> Float
.correlation: (x: Iterable(Float), y: Iterable(Float), method := Str) -> Float
.linear_regression: (x: Iterable(Float), y: Iterable(Float), proportional := Bool) -> NamedTuple { .slope = Float; intercept = Float }