male / female heights data

Description

Body heights of male and female students collected in a classroom experiment.

Usage

data(heights)

Format

A data frame with 7 observations on the following 2 variables.

female

a numeric vector

male

a numeric vector

Author(s)

Dieter Rasch, Juergen Pilz, L.R. Verdooren, Albrecht Gebhardt, Minghui Wang

References

Dieter Rasch, Juergen Pilz, L.R. Verdooren, Albrecht Gebhardt: Optimal Experimental Design with R, Chapman and Hall/CRC, 2011

Examples

data(heights)
attach(heights)
tt <- triangular.test.norm(x=female[1:3],
   y=male[1:3], mu1=170,mu2=176,mu0=164,
   alpha=0.05, beta=0.2,sigma=7)
# Test is yet unfinished, add the remaining values:
tt <- update(tt,x=female[4:7], y=male[4:7])
# Test is finished now

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
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> library(OPDOE)
Loading required package: gmp

Attaching package: 'gmp'

The following objects are masked from 'package:base':

    %*%, apply, crossprod, matrix, tcrossprod

> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/OPDOE/heights.Rd_%03d_medium.png", width=480, height=480)
> ### Name: heights
> ### Title: male / female heights data
> ### Aliases: heights
> ### Keywords: datasets
> 
> ### ** Examples
> 
> data(heights)
> attach(heights)
> tt <- triangular.test.norm(x=female[1:3],
+    y=male[1:3], mu1=170,mu2=176,mu0=164,
+    alpha=0.05, beta=0.2,sigma=7)
Triangular Test for normal distribution

Sigma known: 7 

H0: mu1=mu2= 170  versus H1: mu1= 170  and mu2>= 176  or mu2<= 164 
alpha: 0.05  beta: 0.2 

Test not finished, continue by adding single data via update()
current sample size for x:  3 
current sample size for y:  3 
> # Test is yet unfinished, add the remaining values:
> tt <- update(tt,x=female[4:7], y=male[4:7])
Triangular Test for normal distribution

Sigma known: 7 

H0: mu1=mu2= 170  versus H1: mu1= 170  and mu2>= 176  or mu2<= 164 
alpha: 0.05  beta: 0.2 

Test finished: accept H1 
Sample size for x:  7 
Sample size for y:  7 
> # Test is finished now
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>