# What Can We Understand by the Results of the Kruskal-Wallis Test

## Introduction

The Kruskal-Wallis test also named the Kruskal Wallis H test is the One-way ANOVA test. This test is also termed the nonparametric rank-based test that is used to determine the statistical significance differences between the groups on continuous dependent and independent variables. This test is also termed the Kruskal-Wallis test spss that uses the nonparametric alternative variables, the one-way ANOVA and the extension Mann-Whitney UK test.

## Comparing Multiple Independent Groups and Variables

The Kruskal-Wallis test allows the comparison of more than two or three independent groups and variables, thereby presenting their compared values. For example, the Kruskal-Wallis H test is used for understanding the exam performance that is measured on the continuous scale from the value 0-100 that is different based on the test anxiety level. In this example, the dependent variable presents the exam performance and the independent variable presents the test anxiety level.

Here the students are divided into three levels such as students with low, high and medium anxiety levels. Therefore the Kruskal-Wallis H test is a highly useful statistical technique or tool that uses the SPSS tool to present the comparable values of the two or more variables. Here in example 2, two variables are chosen such as the discrimination towards job opportunities and the social reaction to this discrimination.

The independent variables are present in this Kruskal-Wallis H test as the three levels such as agree, strongly agree and disagree. While the Kruskal-Wallis H test is performed, one-way ANOVA and two-way ANOVA are used to make the comparison among the three levels of independent variables.

For example, here, the one-way ANOVA and two-way ANOVA are used in this kruskal-wallis test spss to compare the reaction of the different social groups to the social discrimination towards job opportunities. The Kruskal-Wallis test spss will show the probability values of each reaction by using the one-way ANOVA and two-way ANOVA to compare the values of the reaction. The one-way ANOVA and two-way ANOVA also use the graphical representation in terms of analysing the comparison between the different variables. The percentage of the different variables are present to present the comparison between all the variables thereby determining authentic and accurate probability values.

## The Evolution and Application of Kruskal-Wallis Test in SPSS

When it comes to discussing the history of the invention of the kruskal-wallis test spss, it must be stated that Kruskal and Wallis proposed this kruskal-wallis test spss in 1952. However, initially, this test was termed as the one-way ANOVA test as the spss data analysis and chi-square test were used to carry out the one-way Mann-Whitney U test among more than two groups. As time passed, the Kruskal-Wallis test spss became highly modified by improving its implementation into the different comparing methods.

As the analogous one-way ANOVA test the Kruskal-Wallis test spss does not conduct the distribution of the normal underlying data, rather it is associated with making thorough comparisons between the two or more dependent and independent variables by presenting their probability values. The spss data analysis and chi-square test are carried out in the Kruskal-Wallis test spss for presenting the post-sequencing microbiome data that are not normally distributed and contain strong outliers or contain the non-normal distribution of data. The Kruskal-Wallis test spss is the omnibus test that cannot tell if the specific groups of the dependent or independent variables are statically important or significantly different from each other. This test uses the
spss data analysis and chi-square test to tell that at least two groups are different from each other.

However, when it comes to determining the difference between the six or seven groups of variables together, the use of spss data analysis and chi-square test is not justified to determine this. The students must know different tools such as spss data analysis and chi-square test, SPSS and the ANOVA to carry out the Kruskal-Wallis H test effectively and accurately to get the compared database among the independent and dependent variables. On the other hand, they also need to have a clear concept of the two-way ANOVA and one-way ANOVA to carry out their test accurately to grab the accurate readings. However, before starting this process, students need to understand that all the assumptions of the data must meet the criteria and guidelines of the Kruskal-Wallis H test for presenting a valid result. While students use the Kruskal-Wallis H test for analysing their data, they need to ensure that the data that are used in the one-way ANOVA and the
SPSS help are accurate and relevant to the Kruskal-Wallis H test process. This is because, in terms of getting valid results, students need to be sure regarding the relevance of the data.

For presenting the valid database, the students need to follow some assumptions such as:

Assumption 1: While using the Kruskal-Wallis H test, students should ensure that their dependent variable is measured at the continuous or ordinal level. For measuring at the ordinal level, students need to use the Likert scale, a 7-point scale that ranges from short agree to strongly disagree. In this process, the Kruskal-Wallis H test is used to use the Likert scale for presenting a valid comparison between three or more variables.

Assumption 2: While using the Kruskal-Wallis H test, the students must ensure that the independent variable contains two or three categories or groups. The Kruskal-Wallis H test is used for comparing three or more categories or independent groups. You can use the spss data analysis, and chi-square test in terms of meeting the criterion of the test and presenting the valid result.

## Conclusion

From this discussion, it can be concluded that the Kruskal-Wallis H test is the most useful tool that is used to make the comparison of two or more dependent and independent variables. This tool uses many techniques such as SPSS, one-way ANOVA, Chi-square test, two-way ANOVA etc. to get a valid result. The Kruskal-Wallis test or kruskal-wallis test spss is also termed as Kruskal-Wallis H test that uses one-way ANOVA, ANOVA, two-way ANOVA, kruskal-wallis test spss, spss data analysis, chi-square test to present valid database.