mean2.ttest | R Documentation |
Given two univariate samples x and y, it tests
H_0 : μ_x^2 ≤ft\lbrace =,≥q,≤q \right\rbrace μ_y^2\quad vs\quad H_1 : μ_x^2 ≤ft\lbrace \neq,<,>\right\rbrace μ_y^2
using the procedure by Student (1908) and Welch (1947).
mean2.ttest( x, y, alternative = c("two.sided", "less", "greater"), paired = FALSE, var.equal = FALSE )
x |
a length-n data vector. |
y |
a length-m data vector. |
alternative |
specifying the alternative hypothesis. |
paired |
a logical; whether consider two samples as paired. |
var.equal |
a logical; if |
a (list) object of S3
class htest
containing:
a test statistic.
p-value under H_0.
alternative hypothesis.
name of the test.
name(s) of provided sample data.
student_probable_1908SHT
\insertRefstudent_probable_1908aSHT
\insertRefwelch_generalization_1947SHT
## empirical Type 1 error niter = 1000 counter = rep(0,niter) # record p-values for (i in 1:niter){ x = rnorm(57) # sample x from N(0,1) y = rnorm(89) # sample y from N(0,1) counter[i] = ifelse(mean2.ttest(x,y)$p.value < 0.05, 1, 0) } ## print the result cat(paste("\n* Example for 'mean2.ttest'\n","*\n", "* number of rejections : ", sum(counter),"\n", "* total number of trials : ", niter,"\n", "* empirical Type 1 error : ",round(sum(counter/niter),5),"\n",sep=""))
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