Plot for distribution of common statistics and p-value

In webr: Data and Functions for Web-Based Analysis

knitr::opts_chunk$set(echo = TRUE,comment = NA,fig.width=6,fig.height = 5, fig.align='center',out.width="90%")

To understand the concept of p value is very important. To teach the the distribution of common statistic( $\chi^2$ for chisq.test() , t for Student's t-test , F for F-test) and concept of the p-value, plot.htest() function can be used.

Package Installation

You can install this package form the github. Currently, package webr is under construction and consists of only one function - plot.htest().

#install.packages("devtools")
devtools::install_github("cardiomoon/webr")

Coverage of plot.htest()

The plot.htest() function is a S3 method for class "htest". Currently, this function covers Welch Two Sample t-test, Pearson's Chi-squared test, Two Sample t-test, One Sample t-test, Paired t-test and F test to compare two variances.

For Chi-squared Test

You can show the distribution of chi-squre statistic and p-value.

 require(moonBook)
 require(webr)

 # chi-squared test
 x=chisq.test(table(acs$sex,acs$DM))
 x
 plot(x)

For one sample t-test

You can show the distribution of t-statistic and p-value in one sample t-test.

t.test(acs$age,mu=63)

plot(t.test(acs$age,mu=63))

Student t-test to compare means for two independent samples

Before performing a t-test, you have to compare two variances.

F test to compare two variances

x=var.test(age~DM,data=acs)
x
plot(x)

Use for Two Sample t-test for independence samples

Based on the result of var.test(), you can perform t.test with default option(var.equal=FALSE).

x=t.test(age~DM,data=acs)
x
plot(x)

Student t-test using pooled variance

To compare means of body-mass index between male and female patients, perform F test first.

var.test(BMI~sex,data=acs)
plot(var.test(BMI~sex,data=acs))

Based on the result of F test, you can perform t-test using pooled variance.

x=t.test(BMI~sex,data=acs,var.equal=TRUE)
x
plot(x)

Paired t-test

You can show the distribution of t-statistic and p-value in paired t-test.

x=t.test(iris$Sepal.Width,iris$Petal.Width,paired=TRUE)
plot(x)

Options for t-test

You can change the options of t.test.

x=t.test(BMI~sex, data=acs,conf.level=0.99,alternative="greater",var.equal=TRUE)
plot(x)

webr documentation built on March 26, 2020, 6:22 p.m.