shiny_twosampt {ABACUS}

Shiny App to Demonstrate Two-Sample Independent (Unpaired) Student's t-Test

Description

An interactive Shiny app to demonstrate two-sample independent (unpaired) Student's t-test.

Usage

shiny_twosampt()

Details

The interactive Shiny app demonstrates the principles of the hypothesis testing of means in a two-sample independent (unpaired) design where the population variances are equal but unknown. The true parameter values are provided by the user. The user changes sample characteristics, distribution function and simulation features and explores the influence of these changes on the hypothesis testing using Student's t-test.

The left panel includes the user inputs for Simulation Features, Population Parameters, Sample Characteristics, and Distribution Function. To use the app at first instance, just click the Update button. To alter the input values, edit the text box or move the point on the slider and explore the changes in different tabs (see below).

To obtain identical outcomes in a separate run of the app, set a common seed value at the bottom of the left panel and click Update. All subsequent updates will produce identical results provided other inputs are identical. The seed value is ignored when the option check the box to update instantly is selected.

Value

The outcomes are presented in several tabs.

Population

contains the density plots of two populations and rug plots of the sample units sample units randomly drawn from these populations. It also includes the population parameter values chosen by the user.

Sample

contains the dot plots and box plots of two samples drawn randomly from the two populations and rug plots of the sample units. It also includes the mean and standard deviation of two random samples.

Test Statistic

contains the plots showing the mean difference between two groups and corresponding 95% confidence intervals (CI). The tab also contains a panel of the distribution of the test statistic t with the observed value of the test statistic and probabilities under the given value of the Type 1 error

Summary

includes the summary of the sampled data and outcomes from the one-sample Student's t-test. Different sections are: (1) Hypothesis, highlighting the null and alternative hypothesis; (2) Sample, tabulating the full sampled data; (3) Summary Statistics, summarising the summary information of two samples; (4) Test Statistic, presenting the outputs from independent two-sample Student's t-test. (5) Confidence Interval, highlighting the mean difference and corresponding 95% confidence intervals (CI).

Note

https://shiny.abdn.ac.uk/Stats/apps/

Author(s)

Mintu Nath

See Also

Function in base R for normal distribution and t distribution including dnorm, pnorm, qnorm, rnorm, dt, pt, qt, rt

Examples

if(interactive()){
    library(ggplot2)
    library(shiny)
    library(ABACUS)
    # Run shiny app
    shiny_twosampt()
}