onewaytests: a web-tool for one-way tests in independent groups designs

Choose a one-way test

Specify the rate of observations trimmed and winsorized from each tail of the distribution

Choose a correction method for pairwise comparisons (*)

(*) Method for adjusting the p-values for pairwise comparisons. However, it adjusts the level of significance for James second order test.

Specify the level of significance

Input data

Load example data:
Upload a delimited text file:

You can upload your data as separated by comma, tab, semicolon or space.

Note: First row must be header.

Choose a variance homogeneity test

Choose a normality test

Specify the level of significance

Choose a plot to assess normality by groups

Choose a plot

Add a violin line

Specify the width of the boxes

Select an option to draw error bars

Specify the width of the little lines

This web-tool enables the applied researchers to investigate treatment effects on dependent variable. In this web-tool, we present the one-way tests in independent groups designs, pairwise comparisons, graphical approaches, and assess variance homogeneity and normality of data in each group via tests and plots.

This web-tool is a web-interface of the onewaytests package in R. The application includes well-known one-way tests in independent groups designs including one-way analysis of variance, Kruskal-Wallis test, Welch heteroscedastic F test, Brown-Forsythe test. In addition to these well-known tests, Alexander-Govern test, James second order test and Welch heteroscedastic F test with trimmed means and Winsorized variances, not available in most statistical software, are able to be reached via this tool. Also, pairwise comparisons can be applied if the statistically significant difference is obtained.

Normality and variance homogeneity are the vital assumptions for the selection of the appropriate test. Therefore, this tool also enables the users to check these assumptions via variance homogeneity and normality tests. Moreover, it enables the users some basic descriptive statistics and graphical approaches.


Usage of the web-tool

(i) load your data set using Data upload tab.

(ii) define response and group variables using Describe data tab.

(iii) check the homogeneity of variance via variance homogeneity tests and normality through normality tests and plots in the Describe data tab. Researchers can also reach the descriptive statistics using this tab.

(iv) compare the groups through one-way tests in independent groups designs and make pairwise comparisons in the One-way tests tab.

(v) obtain the graphics by groups in the Graphics tab.

Users can download normality plots (as pdf) from Describe data tab, graphics (as pdf) from Graphics tab. Users can copy and paste all results in text or word files.

If there are missing values in the data, a listwise deletion will be applied and a complete-case analysis will be performed.


Osman Dag

Department of Biostatistics, Hacettepe University, Ankara, Turkey

Anil Dolgun

School of Science, RMIT University, Melbourne, Australia

N. Meric Konar

Department of Biostatistics, Hacettepe University, Ankara, Turkey


Version 1.2 (September 11, 2018)

(1) Minor visual improvements.

Version 1.1 (October 11, 2017)

(1) Minor improvements and fixes.

Version 1.0 (April 14, 2017)

(1) Web-tool version of the onewaytests package has been released.

Please contact us for any bugs and requests.