diff --git a/doc/api/confint.rst b/doc/api/confint.rst
index 9ba8102d..85cdc47b 100644
--- a/doc/api/confint.rst
+++ b/doc/api/confint.rst
@@ -3,13 +3,15 @@
 Confidence Interval
 ==============================================
 
-.. function:: confint(test::HypothesisTest, alpha=0.05; tail=:both)
+.. function:: confint(test::HypothesisTest, alpha=alpha(test); tail=tail(test))
 
-    Compute a confidence interval C with coverage 1-``alpha``.
+    Compute a confidence interval C with coverage 1-``alpha``
+    (``alpha=0.05`` is the default for all tests, unless alpha is overridden when the test
+    object is created).
 
-    If ``tail`` is ``:both`` (default), then a two-sided confidence
+    If ``tail`` is ``:both``, then a two-sided confidence
     interval is returned. If ``tail`` is ``:left`` or
-    ``:right``, then a one-sided confidence interval is returned
+    ``:right``, then a one-sided confidence interval is returned.
 
     .. note::
       Most of the implemented confidence intervals are *strongly consistent*, that is, the
diff --git a/doc/api/pvalue.rst b/doc/api/pvalue.rst
index 00e30618..db53e896 100644
--- a/doc/api/pvalue.rst
+++ b/doc/api/pvalue.rst
@@ -3,11 +3,11 @@
 p-value
 ==============================================
 
-.. function:: pvalue(test::HypothesisTest; tail=:both)
+.. function:: pvalue(test::HypothesisTest; tail=tail(test))
 
     Compute the p-value for a given significance test.
 
-    If ``tail`` is ``:both`` (default), then the p-value for the
+    If ``tail`` is ``:both``, then the p-value for the
     two-sided test is returned. If ``tail`` is ``:left`` or
     ``:right``, then a one-sided test is performed.
 
diff --git a/doc/parametric/test_t.rst b/doc/parametric/test_t.rst
index ba96b6db..a9b21d08 100644
--- a/doc/parametric/test_t.rst
+++ b/doc/parametric/test_t.rst
@@ -1,16 +1,19 @@
 T-test
 =============================================
 
-.. function:: OneSampleTTest(v::AbstractVector{T<:Real}, mu0::Real=0)
+.. function:: OneSampleTTest(v::AbstractVector{T<:Real}, mu0::Real=0; tail::Symbol=:both, alpha::Real=0.05)
 
     Perform a one sample t-test of the null hypothesis that the data
     in vector ``v`` comes from a distribution with mean ``mu0`` against
     the alternative hypothesis that the distribution does not have mean
     ``mu0``.
 
+    ``tail`` and ``alpha`` specify the defaults when calling
+    :ref:`pvalue<pvalue>` and :ref:`confint<confint>`.
+
     Implements: :ref:`pvalue<pvalue>`, :ref:`confint<confint>`
 
-.. function:: OneSampleTTest(xbar::Real, stdev::Real, n::Int, mu0::Real=0)
+.. function:: OneSampleTTest(xbar::Real, stdev::Real, n::Int, mu0::Real=0; tail::Symbol=:both, alpha::Real=0.05)
 
     Perform a one sample t-test of the null hypothesis that ``n``
     values with mean ``xbar`` and sample standard deviation
@@ -18,9 +21,12 @@ T-test
     the alternative hypothesis that the distribution does not have mean
     ``mu0``.
 
+    ``tail`` and ``alpha`` specify the defaults when calling
+    :ref:`pvalue<pvalue>` and :ref:`confint<confint>`.
+
     Implements: :ref:`pvalue<pvalue>`, :ref:`confint<confint>`
 
-.. function:: OneSampleTTest(x::AbstractVector{T<:Real}, y::AbstractVector{T<:Real}, mu0::Real=0)
+.. function:: OneSampleTTest(x::AbstractVector{T<:Real}, y::AbstractVector{T<:Real}, mu0::Real=0; tail::Symbol=:both, alpha::Real=0.05)
 
     Perform a paired sample t-test of the null hypothesis that
     the differences between pairs of values in vectors ``x`` and
@@ -28,18 +34,24 @@ T-test
     alternative hypothesis that the distribution does not have mean
     ``mu0``.
 
+    ``tail`` and ``alpha`` specify the defaults when calling
+    :ref:`pvalue<pvalue>` and :ref:`confint<confint>`.
+
     Implements: :ref:`pvalue<pvalue>`, :ref:`confint<confint>`
 
-.. function:: EqualVarianceTTest(x::AbstractVector{T<:Real}, y::AbstractVector{T<:Real})
+.. function:: EqualVarianceTTest(x::AbstractVector{T<:Real}, y::AbstractVector{T<:Real}; tail::Symbol=:both, alpha::Real=0.05)
 
     Perform a two-sample t-test of the null hypothesis that
     ``x`` and ``y`` come from a distributions with the same mean
     and equal variances against the alternative hypothesis that the
     distributions have different means and but equal variances.
 
+    ``tail`` and ``alpha`` specify the defaults when calling
+    :ref:`pvalue<pvalue>` and :ref:`confint<confint>`.
+
     Implements: :ref:`pvalue<pvalue>`, :ref:`confint<confint>`
 
-.. function:: UnequalVarianceTTest(x::AbstractVector{T<:Real}, y::AbstractVector{T<:Real})
+.. function:: UnequalVarianceTTest(x::AbstractVector{T<:Real}, y::AbstractVector{T<:Real}; tail::Symbol=:both, alpha::Real=0.05)
 
     Perform an unequal variance two-sample t-test of the null
     hypothesis that ``x`` and ``y`` come from a distributions with
@@ -55,4 +67,7 @@ T-test
         \nu_{\chi'} \approx \frac{\left(\sum_{i=1}^n k_i s_i^2\right)^2}
                                  {\sum_{i=1}^n \frac{(k_i s_i^2)^2}{\nu_i}}
 
+    ``tail`` and ``alpha`` specify the defaults when calling
+    :ref:`pvalue<pvalue>` and :ref:`confint<confint>`.
+
     Implements: :ref:`pvalue<pvalue>`, :ref:`confint<confint>`
diff --git a/src/HypothesisTests.jl b/src/HypothesisTests.jl
index 670b961a..d75f9573 100644
--- a/src/HypothesisTests.jl
+++ b/src/HypothesisTests.jl
@@ -32,7 +32,7 @@ using Rmath: pwilcox, psignrank
 
 import StatsBase.confint
 
-export testname, pvalue, confint
+export testname, pvalue, confint, tail, alpha
 @compat abstract type HypothesisTest end
 
 check_same_length(x::AbstractVector, y::AbstractVector) = if length(x) != length(y)
@@ -72,32 +72,38 @@ end
 function Base.show{T<:HypothesisTest}(io::IO, test::T)
     println(io, testname(test))
     println(io, repeat("-", length(testname(test))))
+    
+    # utilities for pretty-printing
+    conf_string = string(floor((1 - alpha(test)) * 100, 6)) # limit to 6 decimals in %
+    format_detail(label::String, value::Any, len::Int) = # len is max length of label
+        "    " * label * " "^max(len - length(label), 0) * string(value)
 
     # population details
-    has_ci = applicable(StatsBase.confint, test)
+    has_ci = applicable(confint, test)
     (param_name, param_under_h0, param_estimate) = population_param_of_interest(test)
     println(io, "Population details:")
-    println(io, "    parameter of interest:   $param_name")
-    println(io, "    value under h_0:         $param_under_h0")
-    println(io, "    point estimate:          $param_estimate")
+    println(io, format_detail("parameter of interest:", param_name, 32))
+    println(io, format_detail("value under h_0:", param_under_h0, 32))
+    println(io, format_detail("point estimate:", param_estimate, 32))
     if has_ci
-        println(io, "    95% confidence interval: $(StatsBase.confint(test))")
+        println(io, format_detail(conf_string*"% confidence interval:", confint(test), 32))
     end
     println(io)
 
     # test summary
-    p = pvalue(test)
-    outcome = if p > 0.05 "fail to reject" else "reject" end
-    tail = default_tail(test)
-    println(io, "Test summary:")
-    println(io, "    outcome with 95% confidence: $outcome h_0")
-    if tail == :both
-        println(io, "    two-sided p-value:           $p")
-    elseif tail == :left || tail == :right
-        println(io, "    one-sided p-value:           $p")
+    testtail = tail(test)
+    p = pvalue(test) # obeys value of tail(test) if applicable
+    outcome = p > alpha(test) ? "fail to reject" : "reject"
+    if testtail == :both
+        plabel ="two-sided p-value:"
+    elseif testtail == :left || testtail == :right
+        plabel = "one-sided p-value ($(string(testtail)) tail):"
     else
-        println(io, "    p-value:                     $p")
+        plabel = "p-value:"
     end
+    println(io, "Test summary:")
+    println(io, format_detail("outcome with "*conf_string*"% confidence:", outcome*" h_0", 36))
+    println(io, format_detail(plabel, p, 36))
     println(io)
 
     # further details
@@ -108,8 +114,9 @@ end
 # parameter of interest: name, value under h0, point estimate
 population_param_of_interest{T<:HypothesisTest}(test::T) = ("not implemented yet", NaN, NaN)
 
-# is the test one- or two-sided
-default_tail(test::HypothesisTest) = :undefined
+# is the test one- or two-sided?
+tail(test::HypothesisTest)  = :undefined    # overloaded for defaults or field access
+alpha(test::HypothesisTest) = 0.05
 
 function show_params{T<:HypothesisTest}(io::IO, test::T, ident="")
     fieldidx = find(Bool[t<:Number for t in T.types])
diff --git a/src/anderson_darling.jl b/src/anderson_darling.jl
index 14bda655..33e89f75 100644
--- a/src/anderson_darling.jl
+++ b/src/anderson_darling.jl
@@ -35,7 +35,7 @@ function OneSampleADTest{T<:Real}(x::AbstractVector{T}, d::UnivariateDistributio
 end
 
 testname(::OneSampleADTest) = "One sample Anderson-Darling test"
-default_tail(test::OneSampleADTest) = :right
+tail(test::OneSampleADTest) = :right
 
 function show_params(io::IO, x::OneSampleADTest, ident="")
     println(io, ident, "number of observations:   $(x.n)")
@@ -78,7 +78,7 @@ function KSampleADTest{T<:Real}(xs::AbstractVector{T}...; modified=true)
 end
 
 testname(::KSampleADTest) = "k-sample Anderson-Darling test"
-default_tail(test::KSampleADTest) = :right
+tail(test::KSampleADTest) = :right
 
 function show_params(io::IO, x::KSampleADTest, ident="")
     println(io, ident, "number of samples:        $(x.k)")
diff --git a/src/augmented_dickey_fuller.jl b/src/augmented_dickey_fuller.jl
index 3282964e..8e568e00 100644
--- a/src/augmented_dickey_fuller.jl
+++ b/src/augmented_dickey_fuller.jl
@@ -207,6 +207,7 @@ end
 testname(::ADFTest) = "Augmented Dickey-Fuller unit root test"
 population_param_of_interest(x::ADFTest) =
     ("coefficient on lagged non-differenced variable", 0, x.coef)
+tail(test::ADFTest) = :left
 
 function show_params(io::IO, x::ADFTest, ident)
     println(io, ident, "sample size in regression:          ", x.n)
diff --git a/src/binomial.jl b/src/binomial.jl
index 1cac9669..cb8cf3c6 100644
--- a/src/binomial.jl
+++ b/src/binomial.jl
@@ -46,7 +46,7 @@ Returns the string value. E.g. "Binomial test", "Sign Test"
 """
 testname(::BinomialTest) = "Binomial test"
 population_param_of_interest(x::BinomialTest) = ("Probability of success", x.p, x.x/x.n) # parameter of interest: name, value under h0, point estimate
-default_tail(test::BinomialTest) = :both
+tail(test::BinomialTest) = :both
 
 function show_params(io::IO, x::BinomialTest, ident="")
     println(io, ident, "number of observations: $(x.n)")
@@ -157,7 +157,7 @@ SignTest{T<:Real, S<:Real}(x::AbstractVector{T}, y::AbstractVector{S}) = SignTes
 
 testname(::SignTest) = "Sign Test"
 population_param_of_interest(x::SignTest) = ("Median", x.median, median(x.data)) # parameter of interest: name, value under h0, point estimate
-default_tail(test::SignTest) = :both
+tail(test::SignTest) = :both
 
 function show_params(io::IO, x::SignTest, ident="")
     text1 = "number of observations:"
diff --git a/src/box_test.jl b/src/box_test.jl
index c3f43380..7dbbe3a2 100644
--- a/src/box_test.jl
+++ b/src/box_test.jl
@@ -62,7 +62,7 @@ end
 testname(::BoxPierceTest) = "Box-Pierce autocorrelation test"
 population_param_of_interest(x::BoxPierceTest) = ("autocorrelations up to lag k",
     "all zero", NaN)
-default_tail(test::BoxPierceTest) = :right
+tail(test::BoxPierceTest) = :right
 
 function show_params(io::IO, x::BoxPierceTest, ident)
     println(io, ident, "number of observations:         ", x.n)
@@ -111,7 +111,7 @@ end
 testname(::LjungBoxTest) = "Ljung-Box autocorrelation test"
 population_param_of_interest(x::LjungBoxTest) = ("autocorrelations up to lag k",
     "all zero", NaN)
-default_tail(test::LjungBoxTest) = :right
+tail(test::LjungBoxTest) = :right
 
 function show_params(io::IO, x::LjungBoxTest, ident)
     println(io, ident, "number of observations:         ", x.n)
diff --git a/src/breusch_godfrey.jl b/src/breusch_godfrey.jl
index 9d0d2411..7dec9d00 100644
--- a/src/breusch_godfrey.jl
+++ b/src/breusch_godfrey.jl
@@ -68,7 +68,7 @@ end
 testname(::BreuschGodfreyTest) = "Breusch-Godfrey autocorrelation test"
 population_param_of_interest(x::BreuschGodfreyTest) =
     ("coefficients on lagged residuals up to lag p", "all zero", NaN)
-default_tail(test::BreuschGodfreyTest) = :right
+tail(test::BreuschGodfreyTest) = :right
 
 function show_params(io::IO, x::BreuschGodfreyTest, ident)
     println(io, ident, "number of observations:         ", x.n)
diff --git a/src/circular.jl b/src/circular.jl
index 51cbdbcf..555297c2 100644
--- a/src/circular.jl
+++ b/src/circular.jl
@@ -53,7 +53,7 @@ end
 
 testname(::RayleighTest) = "Rayleigh test"
 population_param_of_interest(x::RayleighTest) = ("Mean resultant length", 0, x.Rbar) # parameter of interest: name, value under h0, point estimate
-default_tail(test::RayleighTest) = :both
+tail(test::RayleighTest) = :both
 
 function show_params(io::IO, x::RayleighTest, ident="")
     println(io, ident, "number of observations: $(x.n)")
@@ -99,7 +99,7 @@ FisherTLinearAssociation{S <: Real, T <: Real}(theta::Vector{S},
 testname(::FisherTLinearAssociation) =
     "T-linear test of circular-circular association"
 population_param_of_interest(x::FisherTLinearAssociation) = ("Circular correlation coefficient", 0, x.rho_t) # parameter of interest: name, value under h0, point estimate
-default_tail(test::FisherTLinearAssociation) = :both
+tail(test::FisherTLinearAssociation) = :both
 
 function show_params(io::IO, x::FisherTLinearAssociation, ident="")
     println(io, ident, "number of observations: [$(length(x.theta)),$(length(x.phi))]")
@@ -212,7 +212,7 @@ end
 
 testname(::JammalamadakaCircularCorrelation) = "Jammalamadaka circular correlation"
 population_param_of_interest(x::JammalamadakaCircularCorrelation) = ("Circular-circular correlation coefficient", 0, x.r) # parameter of interest: name, value under h0, point estimate
-default_tail(test::JammalamadakaCircularCorrelation) = :both
+tail(test::JammalamadakaCircularCorrelation) = :both
 
 function show_params(io::IO, x::JammalamadakaCircularCorrelation, ident="")
     println(io, ident, "test statistic: $(x.Z)")
diff --git a/src/deprecated.jl b/src/deprecated.jl
index a44bc037..117ee3f5 100644
--- a/src/deprecated.jl
+++ b/src/deprecated.jl
@@ -1,3 +1,4 @@
 using Base: @deprecate
 
 @deprecate ci(args...) confint(args...)
+@deprecate default_tail(test::HypothesisTest) tail(test)
diff --git a/src/fisher.jl b/src/fisher.jl
index 86b76e25..d98e40bb 100644
--- a/src/fisher.jl
+++ b/src/fisher.jl
@@ -45,7 +45,7 @@ end
 
 testname(::FisherExactTest) = "Fisher's exact test"
 population_param_of_interest(x::FisherExactTest) = ("Odds ratio", 1.0, x.ω) # parameter of interest: name, value under h0, point estimate
-default_tail(test::FisherExactTest) = :both
+tail(test::FisherExactTest) = :both
 
 # The sizing argument to print_matrix was removed during the 0.5 dev period
 if VERSION < v"0.5.0-dev+1936"
diff --git a/src/jarque_bera.jl b/src/jarque_bera.jl
index c55abfe8..c92e9694 100644
--- a/src/jarque_bera.jl
+++ b/src/jarque_bera.jl
@@ -77,7 +77,7 @@ end
 testname(::JarqueBeraTest) = "Jarque-Bera normality test"
 population_param_of_interest(x::JarqueBeraTest) =
     ("skewness and kurtosis", "0 and 3", "$(x.skew) and $(x.kurt)")
-default_tail(test::JarqueBeraTest) = :right
+tail(test::JarqueBeraTest) = :right
 
 function show_params(io::IO, x::JarqueBeraTest, ident)
     println(io, ident, "number of observations:         ", x.n)
diff --git a/src/kolmogorov_smirnov.jl b/src/kolmogorov_smirnov.jl
index 8c0472be..7ddf3de1 100644
--- a/src/kolmogorov_smirnov.jl
+++ b/src/kolmogorov_smirnov.jl
@@ -31,7 +31,7 @@ export
 @compat abstract type ExactKSTest <: KSTest end
 
 population_param_of_interest(x::KSTest) = ("Supremum of CDF differences", 0.0, x.δ) # parameter of interest: name, value under h0, point estimate
-default_tail(test::KSTest) = :both
+tail(test::KSTest) = :both
 
 ## ONE SAMPLE KS-TEST
 
diff --git a/src/kruskal_wallis.jl b/src/kruskal_wallis.jl
index 677e0013..f4f6f182 100644
--- a/src/kruskal_wallis.jl
+++ b/src/kruskal_wallis.jl
@@ -43,7 +43,7 @@ end
 
 testname(::KruskalWallisTest) = "Kruskal-Wallis rank sum test (chi-square approximation)"
 population_param_of_interest(x::KruskalWallisTest) = ("Location parameters", "all equal", NaN) # parameter of interest: name, value under h0, point estimate
-default_tail(test::KruskalWallisTest) = :right
+tail(test::KruskalWallisTest) = :right
 
 function show_params(io::IO, x::KruskalWallisTest, ident)
     println(io, ident, "number of observation in each group: ", x.n_i)
diff --git a/src/mann_whitney.jl b/src/mann_whitney.jl
index 78557525..0653f852 100644
--- a/src/mann_whitney.jl
+++ b/src/mann_whitney.jl
@@ -66,7 +66,7 @@ ExactMannWhitneyUTest{S<:Real,T<:Real}(x::AbstractVector{S}, y::AbstractVector{T
 
 testname(::ExactMannWhitneyUTest) = "Exact Mann-Whitney U test"
 population_param_of_interest(x::ExactMannWhitneyUTest) = ("Location parameter (pseudomedian)", 0, x.median) # parameter of interest: name, value under h0, point estimate
-default_tail(test::ExactMannWhitneyUTest) = :both
+tail(test::ExactMannWhitneyUTest) = :both
 
 function show_params(io::IO, x::ExactMannWhitneyUTest, ident)
     println(io, ident, "number of observations in each group: ", [x.nx, x.ny])
@@ -153,7 +153,7 @@ ApproximateMannWhitneyUTest{S<:Real,T<:Real}(x::AbstractVector{S}, y::AbstractVe
 
 testname(::ApproximateMannWhitneyUTest) = "Approximate Mann-Whitney U test"
 population_param_of_interest(x::ApproximateMannWhitneyUTest) = ("Location parameter (pseudomedian)", 0, x.median) # parameter of interest: name, value under h0, point estimate
-default_tail(test::ApproximateMannWhitneyUTest) = :both
+tail(test::ApproximateMannWhitneyUTest) = :both
 
 function show_params(io::IO, x::ApproximateMannWhitneyUTest, ident)
     println(io, ident, "number of observations in each group: ", [x.nx, x.ny])
diff --git a/src/power_divergence.jl b/src/power_divergence.jl
index ab09fd7f..5c28f80e 100644
--- a/src/power_divergence.jl
+++ b/src/power_divergence.jl
@@ -40,7 +40,7 @@ end
 
 # parameter of interest: name, value under h0, point estimate
 population_param_of_interest(x::PowerDivergenceTest) = ("Multinomial Probabilities", x.theta0, x.thetahat)
-default_tail(test::PowerDivergenceTest) = :right
+tail(test::PowerDivergenceTest) = :right
 
 pvalue(x::PowerDivergenceTest; tail=:right) = pvalue(Chisq(x.df),x.stat; tail=tail)
 
diff --git a/src/t.jl b/src/t.jl
index 313ccbd7..9bcc7432 100644
--- a/src/t.jl
+++ b/src/t.jl
@@ -28,18 +28,18 @@ export OneSampleTTest, TwoSampleTTest, EqualVarianceTTest,
 @compat abstract type TTest <: HypothesisTest end
 @compat abstract type TwoSampleTTest <: TTest end
 
-pvalue(x::TTest; tail=:both) = pvalue(TDist(x.df), x.t; tail=tail)
-
-default_tail(test::TTest) = :both
+pvalue(x::TTest; tail=x.tail) = pvalue(TDist(x.df), x.t; tail=tail)
+tail(x::TTest)  = x.tail    # defaults set by constructors
+alpha(x::TTest) = x.alpha
 
 # confidence interval by inversion
-function StatsBase.confint(x::TTest, alpha::Float64=0.05; tail=:both)
+function StatsBase.confint(x::TTest, alpha::Float64=x.alpha; tail::Symbol=x.tail)
     check_alpha(alpha)
 
     if tail == :left
-        (-Inf, StatsBase.confint(x, alpha*2)[2])
+        (-Inf, StatsBase.confint(x, alpha*2, tail=:both)[2]) # tail=:both blocks infinite recursion
     elseif tail == :right
-        (StatsBase.confint(x, alpha*2)[1], Inf)
+        (StatsBase.confint(x, alpha*2, tail=:both)[1], Inf)
     elseif tail == :both
         q = quantile(TDist(x.df), 1-alpha/2)
         (x.xbar-q*x.stderr, x.xbar+q*x.stderr)
@@ -58,6 +58,8 @@ immutable OneSampleTTest <: TTest
     stderr::Real # empirical standard error
     t::Real      # t-statistic
     μ0::Real     # mean under h_0
+    tail::Symbol # :left, :right, or :both
+    alpha::Real  # alpha value
 end
 
 testname(::OneSampleTTest) = "One sample t-test"
@@ -70,19 +72,21 @@ function show_params(io::IO, x::OneSampleTTest, ident="")
     println(io, ident, "empirical standard error: $(x.stderr)")
 end
 
-function OneSampleTTest(xbar::Real, stddev::Real, n::Int, μ0::Real=0)
+function OneSampleTTest(xbar::Real, stddev::Real, n::Int, μ0::Real=0; tail::Symbol=:both, alpha::Real=0.05)
     stderr = stddev/sqrt(n)
     t = (xbar-μ0)/stderr
     df = n-1
-    OneSampleTTest(n, xbar, df, stderr, t, μ0)
+    OneSampleTTest(n, xbar, df, stderr, t, μ0, tail, alpha)
 end
 
-OneSampleTTest{T<:Real}(v::AbstractVector{T}, μ0::Real=0) = OneSampleTTest(mean(v), std(v), length(v), μ0)
+OneSampleTTest{T<:Real}(v::AbstractVector{T}, μ0::Real=0; tail::Symbol=:both, alpha::Real=0.05) =
+    OneSampleTTest(mean(v), std(v), length(v), μ0, tail=tail, alpha=alpha)
 
-function OneSampleTTest{T<:Real, S<:Real}(x::AbstractVector{T}, y::AbstractVector{S}, μ0::Real=0)
+function OneSampleTTest{T<:Real, S<:Real}(x::AbstractVector{T}, y::AbstractVector{S}, μ0::Real=0;
+                        tail::Symbol=:both, alpha::Real=0.05)
     check_same_length(x, y)
 
-    OneSampleTTest(x - y, μ0)
+    OneSampleTTest(x - y, μ0, tail=tail, alpha=alpha)
 end
 
 
@@ -96,6 +100,8 @@ immutable EqualVarianceTTest <: TwoSampleTTest
     stderr::Real # empirical standard error
     t::Real      # t-statistic
     μ0::Real     # mean difference under h_0
+    tail::Symbol # :left, :right, or :both
+    alpha::Real  # alpha value
 end
 
 function show_params(io::IO, x::TwoSampleTTest, ident="")
@@ -108,14 +114,15 @@ end
 testname(::EqualVarianceTTest) = "Two sample t-test (equal variance)"
 population_param_of_interest(x::TwoSampleTTest) = ("Mean difference", x.μ0, x.xbar) # parameter of interest: name, value under h0, point estimate
 
-function EqualVarianceTTest{T<:Real,S<:Real}(x::AbstractVector{T}, y::AbstractVector{S}, μ0::Real=0)
+function EqualVarianceTTest{T<:Real,S<:Real}(x::AbstractVector{T}, y::AbstractVector{S}, μ0::Real=0;
+                                             tail::Symbol=:both, alpha::Real=0.05)
     nx, ny = length(x), length(y)
     xbar = mean(x) - mean(y)
     stddev = sqrt(((nx - 1) * var(x) + (ny - 1) * var(y)) / (nx + ny - 2))
     stderr = stddev * sqrt(1/nx + 1/ny)
     t = (xbar - μ0) / stderr
     df = nx + ny - 2
-    EqualVarianceTTest(nx, ny, xbar, df, stderr, t, μ0)
+    EqualVarianceTTest(nx, ny, xbar, df, stderr, t, μ0, tail, alpha)
 end
 
 
@@ -129,16 +136,19 @@ immutable UnequalVarianceTTest <: TwoSampleTTest
     stderr::Real # empirical standard error
     t::Real      # t-statistic
     μ0::Real     # mean under h_0
+    tail::Symbol # :left, :right, or :both
+    alpha::Real  # alpha value
 end
 
 testname(::UnequalVarianceTTest) = "Two sample t-test (unequal variance)"
 
-function UnequalVarianceTTest{T<:Real,S<:Real}(x::AbstractVector{T}, y::AbstractVector{S}, μ0::Real=0)
+function UnequalVarianceTTest{T<:Real,S<:Real}(x::AbstractVector{T}, y::AbstractVector{S}, μ0::Real=0;
+                                               tail::Symbol=:both, alpha::Real=0.05)
     nx, ny = length(x), length(y)
     xbar = mean(x)-mean(y)
     varx, vary = var(x), var(y)
     stderr = sqrt(varx/nx + vary/ny)
     t = (xbar-μ0)/stderr
     df = (varx / nx + vary / ny)^2 / ((varx / nx)^2 / (nx - 1) + (vary / ny)^2 / (ny - 1))
-    UnequalVarianceTTest(nx, ny, xbar, df, stderr, t, μ0)
+    UnequalVarianceTTest(nx, ny, xbar, df, stderr, t, μ0, tail, alpha)
 end
diff --git a/src/wilcoxon.jl b/src/wilcoxon.jl
index c1cfe6a2..e5e4f51f 100644
--- a/src/wilcoxon.jl
+++ b/src/wilcoxon.jl
@@ -69,7 +69,7 @@ ExactSignedRankTest{S<:Real,T<:Real}(x::AbstractVector{S}, y::AbstractVector{T})
 
 testname(::ExactSignedRankTest) = "Exact Wilcoxon signed rank test"
 population_param_of_interest(x::ExactSignedRankTest) = ("Location parameter (pseudomedian)", 0, x.median) # parameter of interest: name, value under h0, point estimate
-default_tail(test::ExactSignedRankTest) = :both
+tail(test::ExactSignedRankTest) = :both
 
 function show_params(io::IO, x::ExactSignedRankTest, ident)
     println(io, ident, "number of observations:      ", x.n)
@@ -160,7 +160,7 @@ ApproximateSignedRankTest{S<:Real,T<:Real}(x::AbstractVector{S}, y::AbstractVect
 
 testname(::ApproximateSignedRankTest) = "Approximate Wilcoxon signed rank test"
 population_param_of_interest(x::ApproximateSignedRankTest) = ("Location parameter (pseudomedian)", 0, x.median) # parameter of interest: name, value under h0, point estimate
-default_tail(test::ApproximateSignedRankTest) = :both
+tail(test::ApproximateSignedRankTest) = :both
 
 function show_params(io::IO, x::ApproximateSignedRankTest, ident)
     println(io, ident, "number of observations:      ", x.n)
diff --git a/src/z.jl b/src/z.jl
index 86828f5c..f921f611 100644
--- a/src/z.jl
+++ b/src/z.jl
@@ -30,7 +30,7 @@ export OneSampleZTest, TwoSampleZTest, EqualVarianceZTest,
 
 pvalue(x::ZTest; tail=:both) = pvalue(Normal(0.0, 1.0), x.z; tail=tail)
 
-default_tail(test::ZTest) = :both
+tail(test::ZTest) = :both
 
 # confidence interval by inversion
 function StatsBase.confint(x::ZTest, alpha::Float64=0.05; tail=:both)
diff --git a/test/anderson_darling.jl b/test/anderson_darling.jl
index e48dbe10..b8966cd7 100644
--- a/test/anderson_darling.jl
+++ b/test/anderson_darling.jl
@@ -1,5 +1,5 @@
 using HypothesisTests, Distributions, Base.Test
-using HypothesisTests: default_tail
+using HypothesisTests: tail
 
 # One sample test
 n = 1000
@@ -9,7 +9,7 @@ x = rand(Normal(), n)
 t = OneSampleADTest(x, Normal())
 @test isapprox(t.A², 0.2013, atol=0.1^4)
 @test isapprox(pvalue(t), 0.8811, atol=0.1^4)
-@test default_tail(t) == :right
+@test tail(t) == :right
 
 x = rand(DoubleExponential(), n)
 t = OneSampleADTest(x, Normal())
@@ -36,7 +36,7 @@ t = KSampleADTest(samples...)
 @test isapprox(t.A²k, 8.3926, atol=0.1^4)
 @test isapprox(t.σ, 1.2038, atol=0.1^4)
 @test isapprox(pvalue(t), 0.0020, atol=0.1^4)
-@test default_tail(t) == :right
+@test tail(t) == :right
 
 t = KSampleADTest(samples..., modified = false)
 @test isapprox(t.A²k, 8.3559, atol=0.1^4)
diff --git a/test/binomial.jl b/test/binomial.jl
index 9f80631e..562b1862 100644
--- a/test/binomial.jl
+++ b/test/binomial.jl
@@ -1,11 +1,11 @@
 using HypothesisTests, Base.Test
-using HypothesisTests: default_tail
+using HypothesisTests: tail
 
 t = BinomialTest(26, 78)
 @test pvalue(t) ≈ 0.004334880883507431
 @test pvalue(t, tail=:left) ≈ 0.002167440441753716
 @test pvalue(t, tail=:right) ≈ 0.9989844298129187
-@test default_tail(t) == :both
+@test tail(t) == :both
 @test_ci_approx confint(t) (0.23058523962930383, 0.4491666887959782)
 @test_ci_approx confint(t, tail=:left) (0.0, 0.4313047758370174)
 @test_ci_approx confint(t, tail=:right) (0.2451709633730693, 1.0)
@@ -58,7 +58,7 @@ x = [55, 58, 61, 61, 62, 62, 62, 63, 63, 64, 66, 68, 68, 69, 69, 69, 70, 71, 72,
 @test pvalue(SignTest(x, 70)) ≈ 0.004425048828125003
 @test pvalue(SignTest(x, 70), tail=:left) ≈ 0.0022125244140625013
 @test pvalue(SignTest(x, 70), tail=:right) ≈ 0.9996356964111328
-@test default_tail(SignTest(x)) == :both
+@test tail(SignTest(x)) == :both
 @test_ci_approx confint(SignTest(x, 70)) (62, 69)
 @test_ci_approx confint(SignTest(x, 70), 0.0002) (61, 71)
 show(IOBuffer(), SignTest(x, 70))
diff --git a/test/box_test.jl b/test/box_test.jl
index 364ab1ee..34401952 100644
--- a/test/box_test.jl
+++ b/test/box_test.jl
@@ -1,5 +1,5 @@
 using HypothesisTests, Base.Test
-using HypothesisTests: default_tail
+using HypothesisTests: tail
 
 sim_data_h0=[
     0.297287984535462;0.382395967790608;-0.597634476728231;-0.0104452446373756;
@@ -36,7 +36,7 @@ t = HypothesisTests.BoxPierceTest(sim_data_h0,2,1)
 @test t.dof == 1
 @test t.Q ≈ 1.233942980734545
 @test pvalue(t) ≈ 0.2666415904008932
-@test default_tail(t) == :right
+@test tail(t) == :right
 show(IOBuffer(), t)
 
 t = HypothesisTests.LjungBoxTest(sim_data_h0,5,2)
@@ -46,7 +46,7 @@ t = HypothesisTests.LjungBoxTest(sim_data_h0,5,2)
 @test t.dof == 2
 @test t.Q ≈ 3.2090126519163626
 @test pvalue(t) ≈ 0.36050846449240337
-@test default_tail(t) == :right
+@test tail(t) == :right
 show(IOBuffer(), t)
 
 sim_data_h1 = [
diff --git a/test/breusch_godfrey.jl b/test/breusch_godfrey.jl
index b439524f..e32c049e 100644
--- a/test/breusch_godfrey.jl
+++ b/test/breusch_godfrey.jl
@@ -1,5 +1,5 @@
 using HypothesisTests, Base.Test
-using HypothesisTests: default_tail
+using HypothesisTests: tail
 
 # data simulated under H_1
 data_h1 = [
@@ -114,7 +114,7 @@ t = BreuschGodfreyTest(data_h1[:,2:end],res_vec,4)
 @test t.lag == 4
 @test t.BG ≈ 31.39810637185552
 @test pvalue(t) ≈ 2.5390992557054064e-6
-@test default_tail(t) == :right
+@test tail(t) == :right
 show(IOBuffer(), t)
 
 t = BreuschGodfreyTest(data_h1[:,2:end],res_vec,2,false)
diff --git a/test/circular.jl b/test/circular.jl
index 3eb1b515..1c189485 100644
--- a/test/circular.jl
+++ b/test/circular.jl
@@ -1,5 +1,5 @@
 using HypothesisTests, Base.Test
-using HypothesisTests: default_tail
+using HypothesisTests: tail
 
 # Fisher, 1995 example 4.11
 @test abs(pvalue(RayleighTest(0.2370, 60)) - 0.034) <= 0.001
@@ -13,7 +13,7 @@ t = RayleighTest(
     285, 292, 305, 315, 325, 328, 329, 343, 354, 359]
     *pi/180)
 @test abs(pvalue(t) - 0.20) <= 0.01
-@test default_tail(t) == :both
+@test tail(t) == :both
 show(IOBuffer(), t)
 
 # Fisher, 1995 example 6.8
@@ -28,12 +28,12 @@ wind_direction_12pm =
 t = FisherTLinearAssociation(wind_direction_6am, wind_direction_12pm)
 @test abs(t.rho_t- 0.191) < 0.001
 @test abs(pvalue(t) - 0.01) < 0.01
-@test default_tail(t) == :both
+@test tail(t) == :both
 show(IOBuffer(), t)
 
 # Jammaladak, 2001 example 8.1
 t = JammalamadakaCircularCorrelation(wind_direction_6am, wind_direction_12pm)
 @test abs(t.r - 0.2704648) < 1e-7
 @test abs(pvalue(t) - 0.2247383) < 1e-7
-@test default_tail(t) == :both
+@test tail(t) == :both
 show(IOBuffer(), t)
diff --git a/test/fisher.jl b/test/fisher.jl
index 9652a9b1..2799cabd 100644
--- a/test/fisher.jl
+++ b/test/fisher.jl
@@ -1,5 +1,5 @@
 using HypothesisTests, Base.Test
-using HypothesisTests: default_tail
+using HypothesisTests: tail
 
 t = HypothesisTests.FisherExactTest(1, 1, 1, 1)
 @test t.ω ≈ 1.0
@@ -7,7 +7,7 @@ t = HypothesisTests.FisherExactTest(1, 1, 1, 1)
 @test pvalue(t; tail=:right) ≈ 0.8333333333333337
 @test pvalue(t; method=:central) ≈ 1.0
 @test pvalue(t; method=:minlike) ≈ 1.0
-@test default_tail(t) == :both
+@test tail(t) == :both
 @test_ci_approx confint(t; tail=:left) (0.0, 76.24918299781056)
 @test_ci_approx confint(t; tail=:right) (0.013114894621608135, Inf)
 @test_ci_approx confint(t; method=:central) (0.006400016357911029, 156.2496006379585)
diff --git a/test/jarque_bera.jl b/test/jarque_bera.jl
index df208c91..99a13073 100644
--- a/test/jarque_bera.jl
+++ b/test/jarque_bera.jl
@@ -1,5 +1,5 @@
 using HypothesisTests, Base.Test
-using HypothesisTests: default_tail
+using HypothesisTests: tail
 
 sim_data_h0 = 1.0 .+ [
     0.2972879845354616, 0.3823959677906078, -0.5976344767282311, -0.01044524463737564,
@@ -37,7 +37,7 @@ t = JarqueBeraTest(sim_data_h0)
 @test t.skew ≈ -0.020527653857777352
 @test t.kurt ≈ 2.5117242352057993
 @test pvalue(t) ≈ 0.6003695680393418
-@test default_tail(t) == :right
+@test tail(t) == :right
 show(IOBuffer(), t)
 
 sim_data_h1 = [
@@ -54,5 +54,5 @@ t = JarqueBeraTest(sim_data_h1)
 @test t.skew ≈ 0.11785113019775637
 @test t.kurt ≈ 1.0138888888888888
 @test pvalue(t) ≈ 0.00020338498134114293
-@test default_tail(t) == :right
+@test tail(t) == :right
 show(IOBuffer(), t)
diff --git a/test/kolmogorov_smirnov.jl b/test/kolmogorov_smirnov.jl
index 66fb1170..754b0842 100644
--- a/test/kolmogorov_smirnov.jl
+++ b/test/kolmogorov_smirnov.jl
@@ -14,7 +14,7 @@ t = ApproximateOneSampleKSTest(x, Uniform())
 @test pvalue(t) ≈ 0.6777349664784745
 @test pvalue(t; tail=:left) ≈ 0.849573771973747
 @test pvalue(t; tail=:right) ≈ 0.3545875485608989
-@test default_tail(t) == :both
+@test tail(t) == :both
 show(IOBuffer(), t)
 
 t = ApproximateTwoSampleKSTest(x, [(0:24)/25...])
@@ -24,7 +24,7 @@ t = ApproximateTwoSampleKSTest(x, [(0:24)/25...])
 @test pvalue(t) ≈ 0.993764859699076
 @test pvalue(t; tail=:left) ≈ 0.8521437889662113
 @test pvalue(t; tail=:right) ≈ 0.697676326071031
-@test default_tail(t) == :both
+@test tail(t) == :both
 show(IOBuffer(), t)
 
 t = ExactOneSampleKSTest(x, Uniform())
@@ -34,7 +34,7 @@ t = ExactOneSampleKSTest(x, Uniform())
 @test pvalue(t) ≈ 0.6263437768244742
 @test pvalue(t; tail=:left) ≈ 0.8195705417998183
 @test pvalue(t; tail=:right) ≈ 0.32350648882777194
-@test default_tail(t) == :both
+@test tail(t) == :both
 show(IOBuffer(), t)
 
 ## check fit to normal distribution
diff --git a/test/kruskal_wallis.jl b/test/kruskal_wallis.jl
index b23ecfbe..9e1d2512 100644
--- a/test/kruskal_wallis.jl
+++ b/test/kruskal_wallis.jl
@@ -1,5 +1,5 @@
 using HypothesisTests, Base.Test
-using HypothesisTests: default_tail
+using HypothesisTests: tail
 
 # www.uni-siegen.de/phil/sozialwissenschaften/soziologie/mitarbeiter/ludwig-mayerhofer/statistik/statistik_downloads/statistik_ii_7.pdf
 u5 = [620, 5350, 7220]
@@ -14,7 +14,7 @@ t = HypothesisTests.KruskalWallisTest(u5, u250, u2500, more)
 @test t.H ≈ 1.5803174603174597
 @test t.tie_adjustment == 1
 @test pvalue(t) ≈ 0.6638608922384397
-@test default_tail(t) == :right
+@test tail(t) == :right
 show(IOBuffer(), t)
 
 # http://www.brightstat.com/index.php?option=com_content&task=view&id=41&Itemid=1&limit=1&limitstart=2
diff --git a/test/mann_whitney.jl b/test/mann_whitney.jl
index fae53656..adfda4a0 100644
--- a/test/mann_whitney.jl
+++ b/test/mann_whitney.jl
@@ -1,12 +1,12 @@
 using HypothesisTests, Base.Test
-using HypothesisTests: default_tail
+using HypothesisTests: tail
 
 # Basic exact test
 @test abs(pvalue(ExactMannWhitneyUTest([1:10;], [2.1:2:21;])) - 0.0232) <= 1e-4
 @test abs(pvalue(ExactMannWhitneyUTest([2.1:2:21;], [1:10;])) - 0.0232) <= 1e-4
 @test abs(pvalue(ExactMannWhitneyUTest([1.5:10:100;], [2.1:2:21;])) - 0.0068) <= 1e-4
 @test abs(pvalue(ExactMannWhitneyUTest([2.1:2:21;], [1.5:10:100;])) - 0.0068) <= 1e-4
-@test default_tail(ExactMannWhitneyUTest([1:10;], [2.1:2:21;])) == :both
+@test tail(ExactMannWhitneyUTest([1:10;], [2.1:2:21;])) == :both
 show(IOBuffer(), ExactMannWhitneyUTest([1:10;], [2.1:2:21;]))
 
 # Exact with ties
@@ -28,7 +28,7 @@ show(IOBuffer(), ExactMannWhitneyUTest([1:10;], [2:2:24;]))
 @test abs(pvalue(ApproximateMannWhitneyUTest([2.1:2:21;], [1:10;])) - 0.0257) <= 1e-4
 @test abs(pvalue(ApproximateMannWhitneyUTest([1.5:10:100;], [2.1:2:21;])) - 0.0091) <= 1e-4
 @test abs(pvalue(ApproximateMannWhitneyUTest([2.1:2:21;], [1.5:10:100;])) - 0.0091) <= 1e-4
-@test default_tail(ApproximateMannWhitneyUTest([1:10;], [2.1:2:21;])) == :both
+@test tail(ApproximateMannWhitneyUTest([1:10;], [2.1:2:21;])) == :both
 show(IOBuffer(), ApproximateMannWhitneyUTest([1:10;], [2.1:2:21;]))
 
 # Approximate with ties
diff --git a/test/power_divergence.jl b/test/power_divergence.jl
index 87f1687f..9b8249e2 100644
--- a/test/power_divergence.jl
+++ b/test/power_divergence.jl
@@ -1,6 +1,6 @@
 using HypothesisTests, Base.Test
 using StatsBase
-using HypothesisTests: default_tail
+using HypothesisTests: tail
 
 #Example 1 in R
 #Agresti (2007) p. 39
@@ -26,7 +26,7 @@ for i = 1:length(c)
 end
 
 @test pvalue(m) ≈ 2.9535891832117357e-7
-@test default_tail(m) == :right
+@test tail(m) == :right
 @test m.stat ≈ 30.070149095754687
 @test m.df ≈ 2
 @test m.n ≈ 2757
diff --git a/test/t.jl b/test/t.jl
index efc73583..8d2ecf53 100644
--- a/test/t.jl
+++ b/test/t.jl
@@ -1,5 +1,7 @@
 using HypothesisTests, Base.Test
-using HypothesisTests: default_tail
+using HypothesisTests: tail
+
+iobuffer = IOBuffer() # define once to ease temporary redirection to STDOUT
 
 ## ONE SAMPLE T-TEST
 
@@ -10,8 +12,22 @@ tst = OneSampleTTest(-5:10)
 @test abs(pvalue(tst) - 0.0530) <= 1e-4
 @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
-show(IOBuffer(), tst)
+@test tail(tst) == :both
+show(iobuffer, tst)
+
+tst = OneSampleTTest(-5:10, tail=:left) # specify the tail for the test
+@test abs(pvalue(tst; tail=:both) - 0.0530) <= 1e-4
+@test abs(pvalue(tst) - 0.9735) <= 1e-4 # now tail=:left is the default in pvalue(tst)
+@test abs(pvalue(tst; tail=:right) - 0.0265) <= 1e-4
+@test tail(tst) == :left
+show(iobuffer, tst)
+
+tst = OneSampleTTest(-5:10, tail=:right) # specify the tail for the test
+@test abs(pvalue(tst; tail=:both) - 0.0530) <= 1e-4
+@test abs(pvalue(tst; tail=:left) - 0.9735) <= 1e-4 
+@test abs(pvalue(tst) - 0.0265) <= 1e-4 # now tail=:right is the default in pvalue(tst)
+@test tail(tst) == :right
+show(iobuffer, tst)
 
 tst = OneSampleTTest(mean(-5:10), std(-5:10), 16)
 @test abs(pvalue(tst) - 0.0530) <= 1e-4
@@ -24,7 +40,7 @@ c = confint(tst; tail=:left)
 c = confint(tst; tail=:right)
 @test abs(c[1] - 0.4135) .<= 1e-4
 @test c[2] == Inf
-show(IOBuffer(), tst)
+show(iobuffer, tst)
 
 tst = OneSampleTTest(-10:5)
 @test abs(pvalue(tst) - 0.0530) <= 1e-4
@@ -33,7 +49,17 @@ tst = OneSampleTTest(-10:5)
 @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
-show(IOBuffer(), tst)
+show(iobuffer, tst)
+
+tst = OneSampleTTest(-10:5, tail=:left)
+@test abs.(confint(tst)[2] - (-0.4135)) .<= 1e-4
+@test abs.(confint(tst; tail=:right)[1] - (-4.5865)) .<= 1e-4
+show(iobuffer, tst)
+
+tst = OneSampleTTest(-10:5, tail=:right)
+@test abs.(confint(tst; tail=:left)[2] - (-0.4135)) .<= 1e-4
+@test abs.(confint(tst)[1] - (-4.5865)) .<= 1e-4
+show(iobuffer, tst)
 
 # Paired samples
 @test abs(pvalue(OneSampleTTest([1, 1, 2, 1, 0], [0, 1, 1, 1, 0])) - 0.1778) <= 1e-4
@@ -50,13 +76,25 @@ tst = EqualVarianceTTest(a1, a2)
 @test abs(tst.t - 1.959) <= 1e-3
 @test abs(pvalue(tst) - 0.078) <= 1e-3
 @test all(abs.([confint(tst)...] - [-0.0131, 0.2031]) .<= 1e-4)
-@test default_tail(tst) == :both
-show(IOBuffer(), tst)
+@test tail(tst) == :both
+show(iobuffer, tst)
+
+tst = EqualVarianceTTest(a1, a2, tail=:left)
+@test abs(pvalue(tst) - 0.960) <= 1e-3
+@test abs(pvalue(tst, tail=:both) - 0.078) <= 1e-3
+@test tail(tst) == :left
+show(iobuffer, tst)
 
 tst = UnequalVarianceTTest(a1, a2)
 @test abs(tst.df - 7.03) <= 0.01
 @test abs(tst.t - 1.959) <= 1e-3
 @test abs(pvalue(tst) - 0.091) <= 1e-3
 @test all(abs.([confint(tst)...] - [-0.0196, 0.2096]) .<= 1e-4)
-@test default_tail(tst) == :both
-show(IOBuffer(), tst)
+@test tail(tst) == :both
+show(iobuffer, tst)
+
+tst = UnequalVarianceTTest(a1, a2, tail=:right)
+@test abs(pvalue(tst) - 0.045) <= 1e-3
+@test abs(pvalue(tst, tail=:both) - 0.091) <= 1e-3
+@test tail(tst) == :right
+show(iobuffer, tst)
diff --git a/test/wilcoxon.jl b/test/wilcoxon.jl
index 953ea1f7..9dfeabe9 100644
--- a/test/wilcoxon.jl
+++ b/test/wilcoxon.jl
@@ -1,12 +1,12 @@
 using HypothesisTests, Base.Test
-using HypothesisTests: default_tail
+using HypothesisTests: tail
 
 # Basic exact test
 @test abs(pvalue(ExactSignedRankTest([1:10;], [2:2:20;])) - 0.0020) <= 1e-4
 @test abs(pvalue(ExactSignedRankTest([2:2:20;], [1:10;])) - 0.0020) <= 1e-4
 @test abs(pvalue(ExactSignedRankTest([1:10;], [2:2:16; -1; 1])) - 0.4316) <= 1e-4
 @test abs(pvalue(ExactSignedRankTest([2:2:16; -1; 1], [1:10;])) - 0.4316) <= 1e-4
-@test default_tail(ExactSignedRankTest([1:10;], [2:2:20;])) == :both
+@test tail(ExactSignedRankTest([1:10;], [2:2:20;])) == :both
 show(IOBuffer(), ExactSignedRankTest([1:10;], [2:2:20;]))
 
 # Exact with ties
@@ -22,7 +22,7 @@ show(IOBuffer(), ExactSignedRankTest([1:10;], [1:10;]))
 @test abs(pvalue(ApproximateSignedRankTest([2:2:20;], [1:10;])) - 0.005922) <= 1e-6
 @test abs(pvalue(ApproximateSignedRankTest([1:10;], [2:2:16; -1; 1])) - 0.4148) <= 1e-4
 @test abs(pvalue(ApproximateSignedRankTest([2:2:16; -1; 1], [1:10;])) - 0.4148) <= 1e-4
-@test default_tail(ApproximateSignedRankTest([1:10;], [2:2:20;])) == :both
+@test tail(ApproximateSignedRankTest([1:10;], [2:2:20;])) == :both
 show(IOBuffer(), ApproximateSignedRankTest([1:10;], [2:2:20;]))
 
 # Approximate with ties
@@ -36,7 +36,7 @@ show(IOBuffer(), ApproximateSignedRankTest([1:10;], [1:10;]))
 # # Tests for automatic selection
 @test abs(pvalue(SignedRankTest([1:10;], [2:2:20;])) - 0.0020) <= 1e-4
 @test abs(pvalue(SignedRankTest([1:10;], [2:11;])) - 0.0020) <= 1e-4
-@test default_tail(SignedRankTest([1:10;], [2:2:20;])) == :both
+@test tail(SignedRankTest([1:10;], [2:2:20;])) == :both
 show(IOBuffer(), SignedRankTest([1:10;], [2:2:20;]))
 
 # One Sample tests
diff --git a/test/z.jl b/test/z.jl
index d83be510..d9c2b653 100644
--- a/test/z.jl
+++ b/test/z.jl
@@ -1,6 +1,6 @@
 using HypothesisTests, Base.Test
 using Distributions
-using HypothesisTests: default_tail
+using HypothesisTests: tail
 
 # This is always the null in our tests.
 null = Normal(0.0, 1.0)
@@ -20,7 +20,7 @@ tst = OneSampleZTest(x)
 @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 default_tail(tst) == :both
+@test tail(tst) == :both
 show(IOBuffer(), tst)
 
 tst = OneSampleZTest(m, s, n)
@@ -83,7 +83,7 @@ z = xbar / se
 @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 default_tail(tst) == :both
+@test 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
 show(IOBuffer(), tst)