Tobacco: Tobacco data from Snedecor and Cochran (1967)

In PairedData: Paired Data Analysis

Description

This dataset presents 8 paired data corresponding to numbers of lesions caused by two virus preparations inoculated into the two halves of each tobacco leaves.

Usage

data(Tobacco)

Format

A dataframe with 8 rows and 3 columns:

[,1]	Plant	factor
[,2]	Preparation_1	numeric	number of lesions
[,3]	Preparation_2	numeric	number of lesions

Source

Snedecor, G.W. and Cochran, W.G. (1967) Statistical Methods, 6th ed. Iowa State University Press: Ames.

References

• Pruzek, R.M. & Helmreich, J.E. (2009) Enhancing dependent sample analysis with graphics. Journal of Statistics Education, 17 (1).

• Preece, D.A. (1982) t is for trouble (and textbooks): a critique of some examples of the paired-samples t-test. The Statistician, 31 (2), 169-195.

Examples

data(Tobacco)

# A clear outlier
with(Tobacco,plot(paired(Preparation_1,Preparation_2)))


# Comparison of normal and robust tests
with(Tobacco,t.test(paired(Preparation_1,Preparation_2)))
with(Tobacco,yuen.t.test(paired(Preparation_1,Preparation_2)))

with(Tobacco,Var.test(paired(Preparation_1,Preparation_2)))
with(Tobacco,grambsch.Var.test(paired(Preparation_1,Preparation_2)))

with(Tobacco,cor.test(Preparation_1,Preparation_2))
with(Tobacco,winsor.cor.test(Preparation_1,Preparation_2))

# Maybe a transformation
require(MASS)
with(Tobacco,eqscplot(log(Preparation_1),log(Preparation_2)))
abline(0,1,col="red")

Example output

Loading required package: MASS
Loading required package: gld
Loading required package: mvtnorm
Loading required package: lattice
Loading required package: ggplot2

Attaching package: ‘PairedData’

The following object is masked from ‘package:base’:

    summary


	Paired t-test

data:  Preparation_1 and Preparation_2
t = 2.6253, df = 7, p-value = 0.03414
alternative hypothesis: true difference in means is not equal to 0
95 percent confidence interval:
 0.3972029 7.6027971
sample estimates:
mean of the differences 
                      4 


	Paired Yuen test, trim=0.2

data:  Preparation_1 and Preparation_2
t = 2.7651, df = 5, p-value = 0.0396
alternative hypothesis: true difference in trimmed means is not equal to 0
95 percent confidence interval:
 0.1992708 5.4673959
sample estimates:
trimmed mean of x - trimmed mean of y 
                             2.833333 


	Paired Pitman-Morgan test

data:  Preparation_1 and Preparation_2
t = 2.9146, df = 6, p-value = 0.02682
alternative hypothesis: true ratio of variances is not equal to 1
95 percent confidence interval:
 1.162903 6.366364
sample estimates:
variance of x variance of y 
     66.85714      24.57143 


	Paired Grambsch test

data:  Preparation_1 and Preparation_2
z = 1.4595, p-value = 0.1444
alternative hypothesis: true ratio of variances is not equal to 1


	Pearson's product-moment correlation

data:  Preparation_1 and Preparation_2
t = 5.0218, df = 6, p-value = 0.0024
alternative hypothesis: true correlation is not equal to 0
95 percent confidence interval:
 0.5293983 0.9816982
sample estimates:
      cor 
0.8987792 


	winsorized correlation, trim=0.2

data:  Preparation_1 and Preparation_2
t = 5.994, df = 4, p-value = 0.003897
alternative hypothesis: true (winsorized) correlation is not equal to 0
sample estimates:
      cor 
0.9256882 

PairedData documentation built on May 1, 2019, 6:49 p.m.