From 13ae82ac6b13cb46ce0aae0ec42f6f5fcd5232aa Mon Sep 17 00:00:00 2001
From: pdeffebach <p.deffebach@gmail.com>
Date: Thu, 21 Feb 2019 10:25:04 -0600
Subject: [PATCH 01/12] Add stderror and meandiff functions for TTest

---
 src/t.jl | 5 +++++
 1 file changed, 5 insertions(+)

diff --git a/src/t.jl b/src/t.jl
index e80eeef3..19dd7870 100644
--- a/src/t.jl
+++ b/src/t.jl
@@ -48,6 +48,11 @@ function StatsBase.confint(x::TTest; level::Float64=0.95, tail=:both)
     end
 end
 
+# The standard error of the difference
+StatsBase.stderror(x::TTest) = x.stderr
+
+# The magnitude of the difference
+meandiff(x::TTest) = x.xbar
 
 ## ONE SAMPLE T-TEST
 

From adb6fbe4c5d639cd52eb36513801a6e956e63780 Mon Sep 17 00:00:00 2001
From: pdeffebach <p.deffebach@gmail.com>
Date: Thu, 21 Feb 2019 10:30:52 -0600
Subject: [PATCH 02/12] Same for ZTest

---
 src/z.jl | 6 ++++++
 1 file changed, 6 insertions(+)

diff --git a/src/z.jl b/src/z.jl
index 32d4f1f7..8c6454cf 100644
--- a/src/z.jl
+++ b/src/z.jl
@@ -48,6 +48,12 @@ function StatsBase.confint(x::ZTest; level::Float64=0.95, tail=:both)
     end
 end
 
+# The standard error of the difference
+StatsBase.stderror(x::TTest) = x.stderr
+
+# The magnitude of the difference
+meandiff(x::TTest) = x.xbar
+
 
 ## ONE SAMPLE Z-TEST
 

From 3cd11c2b3200032e6528f11d8b11e564bf6133d3 Mon Sep 17 00:00:00 2001
From: pdeffebach <p.deffebach@gmail.com>
Date: Fri, 3 Jan 2020 19:04:02 -0500
Subject: [PATCH 03/12] test squashing

---
 src/HypothesisTests.jl | 4 ++--
 src/correlation.jl     | 1 +
 src/t.jl               | 3 ---
 src/z.jl               | 4 ----
 4 files changed, 3 insertions(+), 9 deletions(-)

diff --git a/src/HypothesisTests.jl b/src/HypothesisTests.jl
index 4a5cf229..26e9479f 100644
--- a/src/HypothesisTests.jl
+++ b/src/HypothesisTests.jl
@@ -29,9 +29,9 @@ using Distributions, Roots, StatsBase
 using Combinatorics: combinations, permutations
 using Rmath: pwilcox, psignrank
 
-import StatsBase.confint
+import StatsBase.confint, StatsBase.stderror
 
-export testname, pvalue, confint
+export testname, pvalue, confint, stderror
 abstract type HypothesisTest end
 
 check_same_length(x::AbstractVector, y::AbstractVector) = if length(x) != length(y)
diff --git a/src/correlation.jl b/src/correlation.jl
index f1dcb2f1..3c89ea3a 100644
--- a/src/correlation.jl
+++ b/src/correlation.jl
@@ -69,6 +69,7 @@ end
 
 default_tail(::CorrelationTest) = :both
 pvalue(test::CorrelationTest; tail=:both) = pvalue(TDist(dof(test)), test.t, tail=tail)
+StatsBase.stderror(test::CorrelationTest) = sqrt(1/dof(test))
 
 function show_params(io::IO, test::CorrelationTest, indent="")
     println(io, indent, "number of observations:          ", nobs(test))
diff --git a/src/t.jl b/src/t.jl
index 19dd7870..0da81d15 100644
--- a/src/t.jl
+++ b/src/t.jl
@@ -51,9 +51,6 @@ end
 # The standard error of the difference
 StatsBase.stderror(x::TTest) = x.stderr
 
-# The magnitude of the difference
-meandiff(x::TTest) = x.xbar
-
 ## ONE SAMPLE T-TEST
 
 struct OneSampleTTest <: TTest
diff --git a/src/z.jl b/src/z.jl
index 8c6454cf..6fe0c776 100644
--- a/src/z.jl
+++ b/src/z.jl
@@ -51,10 +51,6 @@ end
 # The standard error of the difference
 StatsBase.stderror(x::TTest) = x.stderr
 
-# The magnitude of the difference
-meandiff(x::TTest) = x.xbar
-
-
 ## ONE SAMPLE Z-TEST
 
 struct OneSampleZTest <: ZTest

From caf91fe26660722ec23668f044a3f6cb96330004 Mon Sep 17 00:00:00 2001
From: pdeffebach <p.deffebach@gmail.com>
Date: Fri, 3 Jan 2020 19:17:09 -0500
Subject: [PATCH 04/12] binomial

---
 src/binomial.jl | 5 +++++
 1 file changed, 5 insertions(+)

diff --git a/src/binomial.jl b/src/binomial.jl
index abea8dcf..15f2befd 100644
--- a/src/binomial.jl
+++ b/src/binomial.jl
@@ -65,6 +65,11 @@ function show_params(io::IO, x::BinomialTest, ident="")
 end
 
 pvalue(x::BinomialTest; tail=:both) = pvalue(Binomial(x.n, x.p), x.x; tail=tail)
+function StatsBase.stderror(b::BinomialTest) 
+    n = b.n
+    phat = b.x / n
+    sqrt((phat * (1 - phat)) / n)
+end
 
 # Confidence interval
 """

From d3993fae15a64007c12a67993cd9c2e32beb8c4b Mon Sep 17 00:00:00 2001
From: pdeffebach <p.deffebach@gmail.com>
Date: Fri, 13 Mar 2020 12:38:36 -0400
Subject: [PATCH 05/12] add tests

---
 src/z.jl            | 2 +-
 test/binomial.jl    | 2 ++
 test/correlation.jl | 2 ++
 test/t.jl           | 5 +++++
 test/z.jl           | 7 +++++++
 5 files changed, 17 insertions(+), 1 deletion(-)

diff --git a/src/z.jl b/src/z.jl
index 6fe0c776..1f089ea7 100644
--- a/src/z.jl
+++ b/src/z.jl
@@ -49,7 +49,7 @@ function StatsBase.confint(x::ZTest; level::Float64=0.95, tail=:both)
 end
 
 # The standard error of the difference
-StatsBase.stderror(x::TTest) = x.stderr
+StatsBase.stderror(x::ZTest) = x.stderr
 
 ## ONE SAMPLE Z-TEST
 
diff --git a/test/binomial.jl b/test/binomial.jl
index b0f5197d..902204ea 100644
--- a/test/binomial.jl
+++ b/test/binomial.jl
@@ -6,6 +6,7 @@ using HypothesisTests: default_tail
     @test pvalue(t) ≈ 0.004334880883507431
     @test pvalue(t, tail=:left) ≈ 0.002167440441753716
     @test pvalue(t, tail=:right) ≈ 0.9989844298129187
+    @test stderror(t) ≈ 0.05337605126836238
     @test default_tail(t) == :both
     @test_ci_approx confint(t) (0.23058523962930383, 0.4491666887959782)
     @test_ci_approx confint(t, tail=:left) (0.0, 0.4313047758370174)
@@ -32,6 +33,7 @@ using HypothesisTests: default_tail
     @test pvalue(t) ≈ 0.5078125000000002
     @test pvalue(t, tail=:left) ≈ 0.91015625
     @test pvalue(t, tail=:right) ≈ 0.2539062500000001
+    @test stderror(t) ≈ 0.15713484026367724
     @test_ci_approx confint(t) (0.2992950562085405, 0.9251453685803082)
     @test_ci_approx confint(t, tail=:left) (0.0, 0.9022531865607242)
     @test_ci_approx confint(t, tail=:right) (0.3449413659437032, 1.0)
diff --git a/test/correlation.jl b/test/correlation.jl
index 4c27ed2b..8ee31296 100644
--- a/test/correlation.jl
+++ b/test/correlation.jl
@@ -17,6 +17,7 @@ using StatsBase
     @test nobs(w) == 37
     @test dof(w) == 33
     @test pvalue(w) < 0.00001
+    @test stderror(w) ≈ 0.17407765595569785
 
     X = [ 2 1 0
           4 2 0
@@ -28,4 +29,5 @@ using StatsBase
     @test nobs(x) == 4
     @test dof(x) == 1
     @test pvalue(x) ≈ 0.25776212 atol=1e-6
+    @test stderror(x) ≈ 1.0
 end
diff --git a/test/t.jl b/test/t.jl
index 1f0ccb4b..37fad3f3 100644
--- a/test/t.jl
+++ b/test/t.jl
@@ -11,6 +11,7 @@ using HypothesisTests: default_tail
 	@test abs(pvalue(tst; tail=:left) - 0.9735) <= 1e-4
 	@test abs(pvalue(tst; tail=:right) - 0.0265) <= 1e-4
 	@test default_tail(tst) == :both
+	@test stderror(tst) ≈ tst.stderr ≈ 1.1902380714238083
 	show(IOBuffer(), tst)
 
 	tst = OneSampleTTest(mean(-5:10), std(-5:10), 16)
@@ -24,6 +25,7 @@ using HypothesisTests: default_tail
 	c = confint(tst; tail=:right)
 	@test abs(c[1] - 0.4135) .<= 1e-4
 	@test c[2] == Inf
+	@test stderror(tst) ≈ tst.stderr ≈ 1.1902380714238083
 	show(IOBuffer(), tst)
 
 	tst = OneSampleTTest(-10:5)
@@ -33,6 +35,7 @@ using HypothesisTests: default_tail
 	@test all(abs.([confint(tst)...] - [-5.0369, 0.0369]) .<= 1e-4)
 	@test abs.(confint(tst; tail=:left)[2] - (-0.4135)) .<= 1e-4
 	@test abs.(confint(tst; tail=:right)[1] - (-4.5865)) .<= 1e-4
+	@test stderror(tst) ≈ tst.stderr ≈ 1.1902380714238083	
 	show(IOBuffer(), tst)
 end
 
@@ -52,6 +55,7 @@ end
 	@test abs(pvalue(tst) - 0.078) <= 1e-3
 	@test all(abs.([confint(tst)...] - [-0.0131, 0.2031]) .<= 1e-4)
 	@test default_tail(tst) == :both
+	@test stderror(tst) ≈ tst.stderr ≈ 0.048493985881413015	
 	show(IOBuffer(), tst)
 
 	tst = UnequalVarianceTTest(a1, a2)
@@ -60,6 +64,7 @@ end
 	@test abs(pvalue(tst) - 0.091) <= 1e-3
 	@test all(abs.([confint(tst)...] - [-0.0196, 0.2096]) .<= 1e-4)
 	@test default_tail(tst) == :both
+	@test stderror(tst) ≈ tst.stderr ≈ 0.048493985881413015		
 	show(IOBuffer(), tst)
 end
 end
diff --git a/test/z.jl b/test/z.jl
index faf6eaa8..cb872358 100644
--- a/test/z.jl
+++ b/test/z.jl
@@ -21,6 +21,7 @@ null = Normal(0.0, 1.0)
 	@test pvalue(tst; tail=:left) ≈ cdf(null, z)
 	@test pvalue(tst; tail=:right) ≈ ccdf(null, z)
 	@test default_tail(tst) == :both
+	@test stderror(tst) ≈ tst.stderr ≈ 1.1902380714238083
 	show(IOBuffer(), tst)
 
 	tst = OneSampleZTest(m, s, n)
@@ -33,6 +34,7 @@ null = Normal(0.0, 1.0)
 	@test confint(tst; tail=:left)[2] ≈ m + cquantile(null, 0.05) * se
 	@test confint(tst; tail=:right)[1] ≈ m + quantile(null, 0.05) * se
 	@test confint(tst; tail=:right)[2] ≈ Inf
+	@test stderror(tst) ≈ tst.stderr ≈ 1.1902380714238083
 	show(IOBuffer(), tst)
 
 	x = -10:5
@@ -44,6 +46,7 @@ null = Normal(0.0, 1.0)
 	@test pvalue(tst) ≈ 2 * min(cdf(null, z), ccdf(null, z))
 	@test pvalue(tst; tail=:left) ≈ cdf(null, z)
 	@test pvalue(tst; tail=:right) ≈ ccdf(null, z)
+	@test stderror(tst) ≈ tst.stderr ≈ 1.1902380714238083
 	show(IOBuffer(), tst)
 
 	tst = OneSampleZTest(m, s, n)
@@ -56,6 +59,7 @@ null = Normal(0.0, 1.0)
 	@test confint(tst; tail=:left)[2] ≈ m + cquantile(null, 0.05) * se
 	@test confint(tst; tail=:right)[1] ≈ m + quantile(null, 0.05) * se
 	@test confint(tst; tail=:right)[2] ≈ Inf
+	@test stderror(tst) ≈ tst.stderr ≈ 1.1902380714238083	
 	show(IOBuffer(), tst)
 end
 
@@ -66,6 +70,7 @@ end
 	z = (m - 0) / se
 	tst = OneSampleZTest(x, y)
 	@test pvalue(tst) ≈ 2 * min(cdf(null, z), ccdf(null, z))
+	@test stderror(tst) ≈ tst.stderr ≈ 0.24494897427831783
 end
 
 @testset "Two sample" begin
@@ -87,6 +92,7 @@ end
 	@test default_tail(tst) == :both
 	@test confint(tst)[1] ≈ xbar + quantile(null, 0.05 / 2) * se
 	@test confint(tst)[2] ≈ xbar + cquantile(null, 0.05 / 2) * se
+	@test stderror(tst) ≈ tst.stderr ≈ 0.048493985881413015
 	show(IOBuffer(), tst)
 
 	tst = UnequalVarianceZTest(a1, a2)
@@ -98,6 +104,7 @@ end
 	@test pvalue(tst; tail=:right) ≈ ccdf(null, z)
 	@test confint(tst)[1] ≈ xbar + quantile(null, 0.05 / 2) * se
 	@test confint(tst)[2] ≈ xbar + cquantile(null, 0.05 / 2) * se
+	@test stderror(tst) ≈ tst.stderr ≈ 0.048493985881413015	
 	show(IOBuffer(), tst)
 end
 end

From af6965dc78a7c8acbd5e15fd68770f9e8bb25f56 Mon Sep 17 00:00:00 2001
From: pdeffebach <p.deffebach@gmail.com>
Date: Sun, 29 Mar 2020 16:36:33 -0400
Subject: [PATCH 06/12] Add documentation

---
 src/HypothesisTests.jl |  7 +++++++
 src/binomial.jl        |  2 +-
 src/correlation.jl     |  2 +-
 src/t.jl               | 10 +++++-----
 src/z.jl               | 10 +++++-----
 5 files changed, 19 insertions(+), 12 deletions(-)

diff --git a/src/HypothesisTests.jl b/src/HypothesisTests.jl
index 26e9479f..15ab7c62 100644
--- a/src/HypothesisTests.jl
+++ b/src/HypothesisTests.jl
@@ -68,6 +68,13 @@ If `tail` is `:both` (default), then the p-value for the two-sided test is retur
 """
 function pvalue end
 
+"""
+    stderror(test::HypothesisTest)
+
+Compute the standard error for the point estimate of interest for a test. 
+"""
+function stderror end
+
 # Basic function for finding a p-value given a distribution and tail
 pvalue(dist::ContinuousUnivariateDistribution, x::Number; tail=:both) =
     if tail == :both
diff --git a/src/binomial.jl b/src/binomial.jl
index 15f2befd..f1bcac6e 100644
--- a/src/binomial.jl
+++ b/src/binomial.jl
@@ -45,7 +45,7 @@ probability is not equal to `p`.
 
 Computed confidence intervals ([`confint`](@ref)) by default are Clopper-Pearson intervals.
 
-Implements: [`pvalue`](@ref), [`confint(::BinomialTest)`](@ref)
+Implements: [`pvalue`](@ref), [`confint(::BinomialTest)`](@ref), [`stderror`](@ref)
 """
 BinomialTest(x::AbstractVector{Bool}, p=0.5) =
     BinomialTest(sum(x), length(x), p)
diff --git a/src/correlation.jl b/src/correlation.jl
index 3c89ea3a..f61981a5 100644
--- a/src/correlation.jl
+++ b/src/correlation.jl
@@ -11,7 +11,7 @@ export CorrelationTest
 Perform a t-test for the hypothesis that ``\\text{Cor}(x,y|Z=z) = 0``, i.e. the partial
 correlation of vectors `x` and `y` given the matrix `Z` is zero.
 
-Implements `pvalue` for the t-test.
+Implements `pvalue` for the t-test, as well as `stderror`. 
 Implements `confint` using an approximate confidence interval based on Fisher's
 ``z``-transform.
 
diff --git a/src/t.jl b/src/t.jl
index 0da81d15..dc6fbc19 100644
--- a/src/t.jl
+++ b/src/t.jl
@@ -79,7 +79,7 @@ Perform a one sample t-test of the null hypothesis that `n` values with mean `xb
 sample standard deviation `stddev`  come from a distribution with mean `μ0` against the
 alternative hypothesis that the distribution does not have mean `μ0`.
 
-Implements: [`pvalue`](@ref), [`confint`](@ref)
+Implements: [`pvalue`](@ref), [`confint`](@ref), [`stderror`](@ref)
 """
 function OneSampleTTest(xbar::Real, stddev::Real, n::Int, μ0::Real=0)
     stderr = stddev/sqrt(n)
@@ -95,7 +95,7 @@ Perform a one sample t-test of the null hypothesis that the data in vector `v` c
 a distribution with mean `μ0` against the alternative hypothesis that the distribution
 does not have mean `μ0`.
 
-Implements: [`pvalue`](@ref), [`confint`](@ref)
+Implements: [`pvalue`](@ref), [`confint`](@ref), [`stderror`](@ref)
 """
 OneSampleTTest(v::AbstractVector{T}, μ0::Real=0) where {T<:Real} = OneSampleTTest(mean(v), std(v), length(v), μ0)
 
@@ -106,7 +106,7 @@ Perform a paired sample t-test of the null hypothesis that the differences betwe
 values in vectors `x` and `y` come from a distribution with mean `μ0` against the
 alternative hypothesis that the distribution does not have mean `μ0`.
 
-Implements: [`pvalue`](@ref), [`confint`](@ref)
+Implements: [`pvalue`](@ref), [`confint`](@ref), [`stderror`](@ref)
 """
 function OneSampleTTest(x::AbstractVector{T}, y::AbstractVector{S}, μ0::Real=0) where {T<:Real, S<:Real}
     check_same_length(x, y)
@@ -144,7 +144,7 @@ Perform a two-sample t-test of the null hypothesis that `x` and `y` come from di
 with equal means and variances against the alternative hypothesis that the distributions
 have different means but equal variances.
 
-Implements: [`pvalue`](@ref), [`confint`](@ref)
+Implements: [`pvalue`](@ref), [`confint`](@ref), [`stderror`](@ref)
 """
 function EqualVarianceTTest(x::AbstractVector{T}, y::AbstractVector{S}, μ0::Real=0) where {T<:Real,S<:Real}
     nx, ny = length(x), length(y)
@@ -186,7 +186,7 @@ equation:
         \\frac{(k_i s_i^2)^2}{ν_i}}
 ```
 
-Implements: [`pvalue`](@ref), [`confint`](@ref)
+Implements: [`pvalue`](@ref), [`confint`](@ref), [`stderror`](@ref)
 """
 function UnequalVarianceTTest(x::AbstractVector{T}, y::AbstractVector{S}, μ0::Real=0) where {T<:Real,S<:Real}
     nx, ny = length(x), length(y)
diff --git a/src/z.jl b/src/z.jl
index 1f089ea7..dc68cfa8 100644
--- a/src/z.jl
+++ b/src/z.jl
@@ -77,7 +77,7 @@ Perform a one sample z-test of the null hypothesis that `n` values with mean `xb
 population standard deviation `stddev`  come from a distribution with mean `μ0` against the
 alternative hypothesis that the distribution does not have mean `μ0`.
 
-Implements: [`pvalue`](@ref), [`confint`](@ref)
+Implements: [`pvalue`](@ref), [`confint`](@ref), [`stderror`](@ref)
 """
 function OneSampleZTest(xbar::Real, stddev::Real, n::Int, μ0::Real=0)
     stderr = stddev/sqrt(n)
@@ -92,7 +92,7 @@ Perform a one sample z-test of the null hypothesis that the data in vector `v` c
 a distribution with mean `μ0` against the alternative hypothesis that the distribution
 does not have mean `μ0`.
 
-Implements: [`pvalue`](@ref), [`confint`](@ref)
+Implements: [`pvalue`](@ref), [`confint`](@ref), [`stderror`](@ref)
 """
 OneSampleZTest(v::AbstractVector{T}, μ0::Real=0) where {T<:Real} = OneSampleZTest(mean(v), std(v), length(v), μ0)
 
@@ -103,7 +103,7 @@ Perform a paired sample z-test of the null hypothesis that the differences betwe
 values in vectors `x` and `y` come from a distribution with mean `μ0` against the
 alternative hypothesis that the distribution does not have mean `μ0`.
 
-Implements: [`pvalue`](@ref), [`confint`](@ref)
+Implements: [`pvalue`](@ref), [`confint`](@ref), [`stderror`](@ref)
 """
 function OneSampleZTest(x::AbstractVector{T}, y::AbstractVector{S}, μ0::Real=0) where {T<:Real, S<:Real}
     check_same_length(x, y)
@@ -139,7 +139,7 @@ Perform a two-sample z-test of the null hypothesis that `x` and `y` come from di
 with equal means and variances against the alternative hypothesis that the distributions
 have different means but equal variances.
 
-Implements: [`pvalue`](@ref), [`confint`](@ref)
+Implements: [`pvalue`](@ref), [`confint`](@ref), [`stderror`](@ref)
 """
 function EqualVarianceZTest(x::AbstractVector{T}, y::AbstractVector{S}, μ0::Real=0) where {T<:Real,S<:Real}
     nx, ny = length(x), length(y)
@@ -171,7 +171,7 @@ Perform an unequal variance two-sample z-test of the null hypothesis that `x` an
 from distributions with equal means against the alternative hypothesis that the
 distributions have different means.
 
-Implements: [`pvalue`](@ref), [`confint`](@ref)
+Implements: [`pvalue`](@ref), [`confint`](@ref), [`stderror`](@ref)
 """
 function UnequalVarianceZTest(x::AbstractVector{T}, y::AbstractVector{S}, μ0::Real=0) where {T<:Real,S<:Real}
     nx, ny = length(x), length(y)

From ad0f7d3ce098fc1b376dd852f7d52aefae9f2449 Mon Sep 17 00:00:00 2001
From: pdeffebach <p.deffebach@gmail.com>
Date: Thu, 21 Feb 2019 10:25:04 -0600
Subject: [PATCH 07/12] Add stderror and meandiff functions for TTest

---
 src/t.jl | 5 +++++
 1 file changed, 5 insertions(+)

diff --git a/src/t.jl b/src/t.jl
index e80eeef3..19dd7870 100644
--- a/src/t.jl
+++ b/src/t.jl
@@ -48,6 +48,11 @@ function StatsBase.confint(x::TTest; level::Float64=0.95, tail=:both)
     end
 end
 
+# The standard error of the difference
+StatsBase.stderror(x::TTest) = x.stderr
+
+# The magnitude of the difference
+meandiff(x::TTest) = x.xbar
 
 ## ONE SAMPLE T-TEST
 

From 2417e94e963848285588bf3daceef0ad5caa63bb Mon Sep 17 00:00:00 2001
From: pdeffebach <p.deffebach@gmail.com>
Date: Thu, 21 Feb 2019 10:30:52 -0600
Subject: [PATCH 08/12] Same for ZTest

---
 src/z.jl | 6 ++++++
 1 file changed, 6 insertions(+)

diff --git a/src/z.jl b/src/z.jl
index af3370ef..c48269ca 100644
--- a/src/z.jl
+++ b/src/z.jl
@@ -48,6 +48,12 @@ function StatsBase.confint(x::ZTest; level::Float64=0.95, tail=:both)
     end
 end
 
+# The standard error of the difference
+StatsBase.stderror(x::TTest) = x.stderr
+
+# The magnitude of the difference
+meandiff(x::TTest) = x.xbar
+
 
 ## ONE SAMPLE Z-TEST
 

From 6a35b167a2ff57ef3c380671f2491da4dfc224e1 Mon Sep 17 00:00:00 2001
From: pdeffebach <p.deffebach@gmail.com>
Date: Fri, 3 Jan 2020 19:04:02 -0500
Subject: [PATCH 09/12] test squashing

---
 src/HypothesisTests.jl | 4 ++--
 src/correlation.jl     | 1 +
 src/t.jl               | 3 ---
 src/z.jl               | 4 ----
 4 files changed, 3 insertions(+), 9 deletions(-)

diff --git a/src/HypothesisTests.jl b/src/HypothesisTests.jl
index 8939ca00..63696b86 100644
--- a/src/HypothesisTests.jl
+++ b/src/HypothesisTests.jl
@@ -29,9 +29,9 @@ using Distributions, Roots, StatsBase
 using Combinatorics: combinations, permutations
 using Rmath: pwilcox, psignrank
 
-import StatsBase.confint
+import StatsBase.confint, StatsBase.stderror
 
-export testname, pvalue, confint
+export testname, pvalue, confint, stderror
 abstract type HypothesisTest end
 
 check_same_length(x::AbstractVector, y::AbstractVector) = if length(x) != length(y)
diff --git a/src/correlation.jl b/src/correlation.jl
index 4bbf3233..d5f804c0 100644
--- a/src/correlation.jl
+++ b/src/correlation.jl
@@ -82,6 +82,7 @@ end
 
 default_tail(::CorrelationTest) = :both
 pvalue(test::CorrelationTest; tail=:both) = pvalue(TDist(dof(test)), test.t, tail=tail)
+StatsBase.stderror(test::CorrelationTest) = sqrt(1/dof(test))
 
 function show_params(io::IO, test::CorrelationTest, indent="")
     println(io, indent, "number of observations:          ", nobs(test))
diff --git a/src/t.jl b/src/t.jl
index 19dd7870..0da81d15 100644
--- a/src/t.jl
+++ b/src/t.jl
@@ -51,9 +51,6 @@ end
 # The standard error of the difference
 StatsBase.stderror(x::TTest) = x.stderr
 
-# The magnitude of the difference
-meandiff(x::TTest) = x.xbar
-
 ## ONE SAMPLE T-TEST
 
 struct OneSampleTTest <: TTest
diff --git a/src/z.jl b/src/z.jl
index c48269ca..039dc036 100644
--- a/src/z.jl
+++ b/src/z.jl
@@ -51,10 +51,6 @@ end
 # The standard error of the difference
 StatsBase.stderror(x::TTest) = x.stderr
 
-# The magnitude of the difference
-meandiff(x::TTest) = x.xbar
-
-
 ## ONE SAMPLE Z-TEST
 
 struct OneSampleZTest <: ZTest

From 81596606310434a778918d332128cfab8ca77ecb Mon Sep 17 00:00:00 2001
From: pdeffebach <p.deffebach@gmail.com>
Date: Fri, 3 Jan 2020 19:17:09 -0500
Subject: [PATCH 10/12] binomial

---
 src/binomial.jl | 5 +++++
 1 file changed, 5 insertions(+)

diff --git a/src/binomial.jl b/src/binomial.jl
index abea8dcf..15f2befd 100644
--- a/src/binomial.jl
+++ b/src/binomial.jl
@@ -65,6 +65,11 @@ function show_params(io::IO, x::BinomialTest, ident="")
 end
 
 pvalue(x::BinomialTest; tail=:both) = pvalue(Binomial(x.n, x.p), x.x; tail=tail)
+function StatsBase.stderror(b::BinomialTest) 
+    n = b.n
+    phat = b.x / n
+    sqrt((phat * (1 - phat)) / n)
+end
 
 # Confidence interval
 """

From dfed179e3498e3c5000d7c7dbccefe4b72ac5ebc Mon Sep 17 00:00:00 2001
From: pdeffebach <p.deffebach@gmail.com>
Date: Fri, 13 Mar 2020 12:38:36 -0400
Subject: [PATCH 11/12] add tests

---
 src/z.jl            | 2 +-
 test/binomial.jl    | 2 ++
 test/correlation.jl | 2 ++
 test/t.jl           | 5 +++++
 test/z.jl           | 7 +++++++
 5 files changed, 17 insertions(+), 1 deletion(-)

diff --git a/src/z.jl b/src/z.jl
index 039dc036..567e4201 100644
--- a/src/z.jl
+++ b/src/z.jl
@@ -49,7 +49,7 @@ function StatsBase.confint(x::ZTest; level::Float64=0.95, tail=:both)
 end
 
 # The standard error of the difference
-StatsBase.stderror(x::TTest) = x.stderr
+StatsBase.stderror(x::ZTest) = x.stderr
 
 ## ONE SAMPLE Z-TEST
 
diff --git a/test/binomial.jl b/test/binomial.jl
index b0f5197d..902204ea 100644
--- a/test/binomial.jl
+++ b/test/binomial.jl
@@ -6,6 +6,7 @@ using HypothesisTests: default_tail
     @test pvalue(t) ≈ 0.004334880883507431
     @test pvalue(t, tail=:left) ≈ 0.002167440441753716
     @test pvalue(t, tail=:right) ≈ 0.9989844298129187
+    @test stderror(t) ≈ 0.05337605126836238
     @test default_tail(t) == :both
     @test_ci_approx confint(t) (0.23058523962930383, 0.4491666887959782)
     @test_ci_approx confint(t, tail=:left) (0.0, 0.4313047758370174)
@@ -32,6 +33,7 @@ using HypothesisTests: default_tail
     @test pvalue(t) ≈ 0.5078125000000002
     @test pvalue(t, tail=:left) ≈ 0.91015625
     @test pvalue(t, tail=:right) ≈ 0.2539062500000001
+    @test stderror(t) ≈ 0.15713484026367724
     @test_ci_approx confint(t) (0.2992950562085405, 0.9251453685803082)
     @test_ci_approx confint(t, tail=:left) (0.0, 0.9022531865607242)
     @test_ci_approx confint(t, tail=:right) (0.3449413659437032, 1.0)
diff --git a/test/correlation.jl b/test/correlation.jl
index d2686378..d7111741 100644
--- a/test/correlation.jl
+++ b/test/correlation.jl
@@ -41,6 +41,7 @@ end
     @test nobs(w) == 37
     @test dof(w) == 33
     @test pvalue(w) < 0.00001
+    @test stderror(w) ≈ 0.17407765595569785
 
     X = [ 2 1 0
           4 2 0
@@ -52,4 +53,5 @@ end
     @test nobs(x) == 4
     @test dof(x) == 1
     @test pvalue(x) ≈ 0.25776212 atol=1e-6
+    @test stderror(x) ≈ 1.0
 end
diff --git a/test/t.jl b/test/t.jl
index 1f0ccb4b..37fad3f3 100644
--- a/test/t.jl
+++ b/test/t.jl
@@ -11,6 +11,7 @@ using HypothesisTests: default_tail
 	@test abs(pvalue(tst; tail=:left) - 0.9735) <= 1e-4
 	@test abs(pvalue(tst; tail=:right) - 0.0265) <= 1e-4
 	@test default_tail(tst) == :both
+	@test stderror(tst) ≈ tst.stderr ≈ 1.1902380714238083
 	show(IOBuffer(), tst)
 
 	tst = OneSampleTTest(mean(-5:10), std(-5:10), 16)
@@ -24,6 +25,7 @@ using HypothesisTests: default_tail
 	c = confint(tst; tail=:right)
 	@test abs(c[1] - 0.4135) .<= 1e-4
 	@test c[2] == Inf
+	@test stderror(tst) ≈ tst.stderr ≈ 1.1902380714238083
 	show(IOBuffer(), tst)
 
 	tst = OneSampleTTest(-10:5)
@@ -33,6 +35,7 @@ using HypothesisTests: default_tail
 	@test all(abs.([confint(tst)...] - [-5.0369, 0.0369]) .<= 1e-4)
 	@test abs.(confint(tst; tail=:left)[2] - (-0.4135)) .<= 1e-4
 	@test abs.(confint(tst; tail=:right)[1] - (-4.5865)) .<= 1e-4
+	@test stderror(tst) ≈ tst.stderr ≈ 1.1902380714238083	
 	show(IOBuffer(), tst)
 end
 
@@ -52,6 +55,7 @@ end
 	@test abs(pvalue(tst) - 0.078) <= 1e-3
 	@test all(abs.([confint(tst)...] - [-0.0131, 0.2031]) .<= 1e-4)
 	@test default_tail(tst) == :both
+	@test stderror(tst) ≈ tst.stderr ≈ 0.048493985881413015	
 	show(IOBuffer(), tst)
 
 	tst = UnequalVarianceTTest(a1, a2)
@@ -60,6 +64,7 @@ end
 	@test abs(pvalue(tst) - 0.091) <= 1e-3
 	@test all(abs.([confint(tst)...] - [-0.0196, 0.2096]) .<= 1e-4)
 	@test default_tail(tst) == :both
+	@test stderror(tst) ≈ tst.stderr ≈ 0.048493985881413015		
 	show(IOBuffer(), tst)
 end
 end
diff --git a/test/z.jl b/test/z.jl
index faf6eaa8..cb872358 100644
--- a/test/z.jl
+++ b/test/z.jl
@@ -21,6 +21,7 @@ null = Normal(0.0, 1.0)
 	@test pvalue(tst; tail=:left) ≈ cdf(null, z)
 	@test pvalue(tst; tail=:right) ≈ ccdf(null, z)
 	@test default_tail(tst) == :both
+	@test stderror(tst) ≈ tst.stderr ≈ 1.1902380714238083
 	show(IOBuffer(), tst)
 
 	tst = OneSampleZTest(m, s, n)
@@ -33,6 +34,7 @@ null = Normal(0.0, 1.0)
 	@test confint(tst; tail=:left)[2] ≈ m + cquantile(null, 0.05) * se
 	@test confint(tst; tail=:right)[1] ≈ m + quantile(null, 0.05) * se
 	@test confint(tst; tail=:right)[2] ≈ Inf
+	@test stderror(tst) ≈ tst.stderr ≈ 1.1902380714238083
 	show(IOBuffer(), tst)
 
 	x = -10:5
@@ -44,6 +46,7 @@ null = Normal(0.0, 1.0)
 	@test pvalue(tst) ≈ 2 * min(cdf(null, z), ccdf(null, z))
 	@test pvalue(tst; tail=:left) ≈ cdf(null, z)
 	@test pvalue(tst; tail=:right) ≈ ccdf(null, z)
+	@test stderror(tst) ≈ tst.stderr ≈ 1.1902380714238083
 	show(IOBuffer(), tst)
 
 	tst = OneSampleZTest(m, s, n)
@@ -56,6 +59,7 @@ null = Normal(0.0, 1.0)
 	@test confint(tst; tail=:left)[2] ≈ m + cquantile(null, 0.05) * se
 	@test confint(tst; tail=:right)[1] ≈ m + quantile(null, 0.05) * se
 	@test confint(tst; tail=:right)[2] ≈ Inf
+	@test stderror(tst) ≈ tst.stderr ≈ 1.1902380714238083	
 	show(IOBuffer(), tst)
 end
 
@@ -66,6 +70,7 @@ end
 	z = (m - 0) / se
 	tst = OneSampleZTest(x, y)
 	@test pvalue(tst) ≈ 2 * min(cdf(null, z), ccdf(null, z))
+	@test stderror(tst) ≈ tst.stderr ≈ 0.24494897427831783
 end
 
 @testset "Two sample" begin
@@ -87,6 +92,7 @@ end
 	@test default_tail(tst) == :both
 	@test confint(tst)[1] ≈ xbar + quantile(null, 0.05 / 2) * se
 	@test confint(tst)[2] ≈ xbar + cquantile(null, 0.05 / 2) * se
+	@test stderror(tst) ≈ tst.stderr ≈ 0.048493985881413015
 	show(IOBuffer(), tst)
 
 	tst = UnequalVarianceZTest(a1, a2)
@@ -98,6 +104,7 @@ end
 	@test pvalue(tst; tail=:right) ≈ ccdf(null, z)
 	@test confint(tst)[1] ≈ xbar + quantile(null, 0.05 / 2) * se
 	@test confint(tst)[2] ≈ xbar + cquantile(null, 0.05 / 2) * se
+	@test stderror(tst) ≈ tst.stderr ≈ 0.048493985881413015	
 	show(IOBuffer(), tst)
 end
 end

From 7b29eb262f16257b1758b28b1f2aa365224070ac Mon Sep 17 00:00:00 2001
From: pdeffebach <p.deffebach@gmail.com>
Date: Sun, 29 Mar 2020 16:36:33 -0400
Subject: [PATCH 12/12] Add documentation

---
 src/HypothesisTests.jl |  7 +++++++
 src/binomial.jl        |  2 +-
 src/correlation.jl     |  2 +-
 src/t.jl               | 10 +++++-----
 src/z.jl               | 10 +++++-----
 5 files changed, 19 insertions(+), 12 deletions(-)

diff --git a/src/HypothesisTests.jl b/src/HypothesisTests.jl
index 63696b86..5c0f6094 100644
--- a/src/HypothesisTests.jl
+++ b/src/HypothesisTests.jl
@@ -68,6 +68,13 @@ If `tail` is `:both` (default), then the p-value for the two-sided test is retur
 """
 function pvalue end
 
+"""
+    stderror(test::HypothesisTest)
+
+Compute the standard error for the point estimate of interest for a test. 
+"""
+function stderror end
+
 # Basic function for finding a p-value given a distribution and tail
 pvalue(dist::ContinuousUnivariateDistribution, x::Number; tail=:both) =
     if tail == :both
diff --git a/src/binomial.jl b/src/binomial.jl
index 15f2befd..f1bcac6e 100644
--- a/src/binomial.jl
+++ b/src/binomial.jl
@@ -45,7 +45,7 @@ probability is not equal to `p`.
 
 Computed confidence intervals ([`confint`](@ref)) by default are Clopper-Pearson intervals.
 
-Implements: [`pvalue`](@ref), [`confint(::BinomialTest)`](@ref)
+Implements: [`pvalue`](@ref), [`confint(::BinomialTest)`](@ref), [`stderror`](@ref)
 """
 BinomialTest(x::AbstractVector{Bool}, p=0.5) =
     BinomialTest(sum(x), length(x), p)
diff --git a/src/correlation.jl b/src/correlation.jl
index d5f804c0..a1d68c9e 100644
--- a/src/correlation.jl
+++ b/src/correlation.jl
@@ -16,7 +16,7 @@ of vectors `x` and `y` is zero.
 Perform a t-test for the hypothesis that ``\\text{Cor}(x,y|Z=z) = 0``, i.e. the partial
 correlation of vectors `x` and `y` given the matrix `Z` is zero.
 
-Implements `pvalue` for the t-test.
+Implements `pvalue` for the t-test, as well as `stderror`. 
 Implements `confint` using an approximate confidence interval based on Fisher's
 ``z``-transform.
 
diff --git a/src/t.jl b/src/t.jl
index 0da81d15..dc6fbc19 100644
--- a/src/t.jl
+++ b/src/t.jl
@@ -79,7 +79,7 @@ Perform a one sample t-test of the null hypothesis that `n` values with mean `xb
 sample standard deviation `stddev`  come from a distribution with mean `μ0` against the
 alternative hypothesis that the distribution does not have mean `μ0`.
 
-Implements: [`pvalue`](@ref), [`confint`](@ref)
+Implements: [`pvalue`](@ref), [`confint`](@ref), [`stderror`](@ref)
 """
 function OneSampleTTest(xbar::Real, stddev::Real, n::Int, μ0::Real=0)
     stderr = stddev/sqrt(n)
@@ -95,7 +95,7 @@ Perform a one sample t-test of the null hypothesis that the data in vector `v` c
 a distribution with mean `μ0` against the alternative hypothesis that the distribution
 does not have mean `μ0`.
 
-Implements: [`pvalue`](@ref), [`confint`](@ref)
+Implements: [`pvalue`](@ref), [`confint`](@ref), [`stderror`](@ref)
 """
 OneSampleTTest(v::AbstractVector{T}, μ0::Real=0) where {T<:Real} = OneSampleTTest(mean(v), std(v), length(v), μ0)
 
@@ -106,7 +106,7 @@ Perform a paired sample t-test of the null hypothesis that the differences betwe
 values in vectors `x` and `y` come from a distribution with mean `μ0` against the
 alternative hypothesis that the distribution does not have mean `μ0`.
 
-Implements: [`pvalue`](@ref), [`confint`](@ref)
+Implements: [`pvalue`](@ref), [`confint`](@ref), [`stderror`](@ref)
 """
 function OneSampleTTest(x::AbstractVector{T}, y::AbstractVector{S}, μ0::Real=0) where {T<:Real, S<:Real}
     check_same_length(x, y)
@@ -144,7 +144,7 @@ Perform a two-sample t-test of the null hypothesis that `x` and `y` come from di
 with equal means and variances against the alternative hypothesis that the distributions
 have different means but equal variances.
 
-Implements: [`pvalue`](@ref), [`confint`](@ref)
+Implements: [`pvalue`](@ref), [`confint`](@ref), [`stderror`](@ref)
 """
 function EqualVarianceTTest(x::AbstractVector{T}, y::AbstractVector{S}, μ0::Real=0) where {T<:Real,S<:Real}
     nx, ny = length(x), length(y)
@@ -186,7 +186,7 @@ equation:
         \\frac{(k_i s_i^2)^2}{ν_i}}
 ```
 
-Implements: [`pvalue`](@ref), [`confint`](@ref)
+Implements: [`pvalue`](@ref), [`confint`](@ref), [`stderror`](@ref)
 """
 function UnequalVarianceTTest(x::AbstractVector{T}, y::AbstractVector{S}, μ0::Real=0) where {T<:Real,S<:Real}
     nx, ny = length(x), length(y)
diff --git a/src/z.jl b/src/z.jl
index 567e4201..ad719b04 100644
--- a/src/z.jl
+++ b/src/z.jl
@@ -77,7 +77,7 @@ Perform a one sample z-test of the null hypothesis that `n` values with mean `xb
 population standard deviation `stddev`  come from a distribution with mean `μ0` against the
 alternative hypothesis that the distribution does not have mean `μ0`.
 
-Implements: [`pvalue`](@ref), [`confint`](@ref)
+Implements: [`pvalue`](@ref), [`confint`](@ref), [`stderror`](@ref)
 """
 function OneSampleZTest(xbar::Real, stddev::Real, n::Int, μ0::Real=0)
     stderr = stddev/sqrt(n)
@@ -92,7 +92,7 @@ Perform a one sample z-test of the null hypothesis that the data in vector `v` c
 a distribution with mean `μ0` against the alternative hypothesis that the distribution
 does not have mean `μ0`.
 
-Implements: [`pvalue`](@ref), [`confint`](@ref)
+Implements: [`pvalue`](@ref), [`confint`](@ref), [`stderror`](@ref)
 """
 OneSampleZTest(v::AbstractVector{T}, μ0::Real=0) where {T<:Real} = OneSampleZTest(mean(v), std(v), length(v), μ0)
 
@@ -103,7 +103,7 @@ Perform a paired sample z-test of the null hypothesis that the differences betwe
 values in vectors `x` and `y` come from a distribution with mean `μ0` against the
 alternative hypothesis that the distribution does not have mean `μ0`.
 
-Implements: [`pvalue`](@ref), [`confint`](@ref)
+Implements: [`pvalue`](@ref), [`confint`](@ref), [`stderror`](@ref)
 """
 function OneSampleZTest(x::AbstractVector{T}, y::AbstractVector{S}, μ0::Real=0) where {T<:Real, S<:Real}
     check_same_length(x, y)
@@ -139,7 +139,7 @@ Perform a two-sample z-test of the null hypothesis that `x` and `y` come from di
 with equal means and variances against the alternative hypothesis that the distributions
 have different means but equal variances.
 
-Implements: [`pvalue`](@ref), [`confint`](@ref)
+Implements: [`pvalue`](@ref), [`confint`](@ref), [`stderror`](@ref)
 """
 function EqualVarianceZTest(x::AbstractVector{T}, y::AbstractVector{S}, μ0::Real=0) where {T<:Real,S<:Real}
     nx, ny = length(x), length(y)
@@ -171,7 +171,7 @@ Perform an unequal variance two-sample z-test of the null hypothesis that `x` an
 from distributions with equal means against the alternative hypothesis that the
 distributions have different means.
 
-Implements: [`pvalue`](@ref), [`confint`](@ref)
+Implements: [`pvalue`](@ref), [`confint`](@ref), [`stderror`](@ref)
 """
 function UnequalVarianceZTest(x::AbstractVector{T}, y::AbstractVector{S}, μ0::Real=0) where {T<:Real,S<:Real}
     nx, ny = length(x), length(y)