Two sample location tests
test-locationTest.RdTests if two series differ in their distributional location parameter.
Usage
locationTest(x, y, method = c("t", "kw2"), title = NULL,
    description = NULL)Details
The method = "t" can be used to determine if the two sample
  means are equal for unpaired data sets. Two variants are used,
  assuming equal or unequal variances.
The method = "kw2" performs a Kruskal-Wallis rank sum
  test of the null hypothesis that the central tendencies or medians of
  two samples are the same. The alternative is that they differ.
  Note, that it is not assumed that the two samples are drawn from the
  same distribution. It is also worth to know that the test assumes
  that the variables under consideration have underlying continuous
  distributions.
Value
an object from class fHTEST
References
Conover, W. J. (1971); Practical nonparametric statistics, New York: John Wiley & Sons.
Lehmann E.L. (1986); Testing Statistical Hypotheses, John Wiley and Sons, New York.
Examples
x <- rnorm(50)
y <- rnorm(50)
  
locationTest(x, y, "t")
#> 
#> Title:
#>  t Test
#> 
#> Test Results:
#>   PARAMETER:
#>     x Observations: 50
#>     y Observations: 50
#>     mu: 0
#>   SAMPLE ESTIMATES:
#>     Mean of x: 0.2137
#>     Mean of y: -0.2064
#>     Var  of x: 0.8717
#>     Var  of y: 0.672
#>   STATISTIC:
#>                 T: 2.3905
#>     T | Equal Var: 2.3905
#>   P VALUE:
#>     Alternative Two-Sided: 0.01877 
#>     Alternative      Less: 0.9906 
#>     Alternative   Greater: 0.009384 
#>     Alternative Two-Sided | Equal Var: 0.01873 
#>     Alternative      Less | Equal Var: 0.9906 
#>     Alternative   Greater | Equal Var: 0.009367 
#>   CONFIDENCE INTERVAL:
#>     Two-Sided: 0.0713, 0.7688
#>          Less: -Inf, 0.7119
#>       Greater: 0.1282, Inf
#>     Two-Sided | Equal Var: 0.0714, 0.7687
#>          Less | Equal Var: -Inf, 0.7118
#>       Greater | Equal Var: 0.1283, Inf
#> 
locationTest(x, y, "kw2")
#> 
#> Title:
#>  Kruskal-Wallis Two Sample Test
#> 
#> Test Results:
#>   PARAMETER:
#>     x Observations: 50
#>     y Observations: 50
#>   SAMPLE ESTIMATES:
#>     Mean of x: 0.2137
#>     Mean of y: -0.2064
#>     Var  of x: 0.8717
#>     Var  of y: 0.672
#>   STATISTIC:
#>     KW chi-squared: 4.7156
#>   P VALUE:
#>     0.02989 
#>