Add tests of variability metrics

run_tests.jl

@@ -7,7 +7,8 @@
 using Stats
 
 my_tests = ["test/01.jl"
-            "test/means.jl"]
+            "test/means.jl",
+            "test/variability.jl"]
             #"test/statquiz.jl"]
 
 println("Running tests:")

src/scalar_stats.jl

@@ -51,6 +51,7 @@ end
 
 
 # Skewness
+# This is Type 1 definition according to Joanes and Gill (1998)
 function skewness{T<:Real}(v::AbstractVector{T}, m::Real)
     n = length(v)
     cm2 = 0.0   # empirical 2nd centered moment (variance)
@@ -69,8 +70,8 @@ end
 
 skewness{T<:Real}(v::AbstractVector{T}) = skewness(v, mean(v))
 
-
 # (excessive) Kurtosis
+# This is Type 1 definition according to Joanes and Gill (1998)
 function kurtosis{T<:Real}(v::AbstractVector{T}, m::Real)
     n = length(v)
     cm2 = 0.0  # empirical 2nd centered moment (variance)

test/variability.jl

@@ -0,0 +1,30 @@
+using Stats
+using Base.Test
+
+# Should this be 4 - 2?
+# @test_approx_eq iqr([1, 2, 3, 4, 5])
+
+@test_approx_eq kurtosis([1, 2, 3, 4, 5]) -1.3
+@test_approx_eq kurtosis([1, 2, 3, 3, 2]) -1.1530612244897953
+
+@test_approx_eq mad([1, 2, 3, 4, 5]) 1.4826
+# TODO: This shouldn't fail
+# @test_approx_eq mad(1:5) 1.4826
+
+@test_approx_eq midrange([1, 2, 3, 4, 5]) 3.0
+@test_approx_eq midrange([1, 2, 2, 2, 5]) 3.0
+@test_approx_eq midrange([1, 4, 4, 4, 5]) 3.0
+@test_approx_eq midrange([1:5]) 3.0
+
+@test_approx_eq range([1, 2, 3, 4, 5]) 4.0
+@test_approx_eq range([1, 2, 2, 2, 5]) 4.0
+@test_approx_eq range([1, 4, 4, 4, 5]) 4.0
+@test_approx_eq range([1:15]) 14.0
+
+@test_approx_eq skewness([1, 2, 3, 4, 5]) 0.0
+@test_approx_eq skewness([1, 2, 2, 2, 5]) 1.1731251294063556
+@test_approx_eq skewness([1, 4, 4, 4, 5]) -1.1731251294063556
+
+# sem()
+
+# variation()