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