Ttest¶

OneSampleTTest
(v::AbstractVector{T<:Real}, mu0::Real=0)¶ Perform a one sample ttest of the null hypothesis that the data in vector
v
comes from a distribution with meanmu0
against the alternative hypothesis that the distribution does not have meanmu0
.Implements: pvalue, confint

OneSampleTTest
(xbar::Real, stdev::Real, n::Int, mu0::Real=0) Perform a one sample ttest of the null hypothesis that
n
values with meanxbar
and sample standard deviationstdev
come from a distribution withmu0
against the alternative hypothesis that the distribution does not have meanmu0
.Implements: pvalue, confint

OneSampleTTest
(x::AbstractVector{T<:Real}, y::AbstractVector{T<:Real}, mu0::Real=0) Perform a paired sample ttest of the null hypothesis that the differences between pairs of values in vectors
x
andy
come from a distribution withmu0
against the alternative hypothesis that the distribution does not have meanmu0
.Implements: pvalue, confint

EqualVarianceTTest
(x::AbstractVector{T<:Real}, y::AbstractVector{T<:Real})¶ Perform a twosample ttest of the null hypothesis that
x
andy
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.Implements: pvalue, confint

UnequalVarianceTTest
(x::AbstractVector{T<:Real}, y::AbstractVector{T<:Real})¶ Perform an unequal variance twosample ttest of the null hypothesis that
x
andy
come from a distributions with the same mean against the alternative hypothesis that the distributions have different means.This test is also known as sometimes known as Welch’s ttest. It differs from the equal variance ttest in that it computes the number of degrees of freedom of the test using the WelchSatterthwaite equation:
\[\nu_{\chi'} \approx \frac{\left(\sum_{i=1}^n k_i s_i^2\right)^2} {\sum_{i=1}^n \frac{(k_i s_i^2)^2}{\nu_i}}\]Implements: pvalue, confint