Why should I use a Kruskal-Wallis test? (With Minitab) Why should I use a Kruskal-Wallis test? (With SPSS)

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1 Why should I use a Kruskal-Wallis test? (With Minitab) To perform this test, select Stat > Nonparametrics > Kruskal-Wallis. Use the Kruskal-Wallis test to determine whether the medians of two or more groups differ when you have data that are not symmetric, such as skewed data. The Kruskal-Wallis test is a nonparametric alternative to a one-way ANOVA. The test does not require the data to be normal, but instead uses the rank of the data values instead of the actual data values for the analysis. For example, a health administrator wants to compare the unoccupied bed space for three hospitals in the same city. For Kruskal-Wallis, the hypotheses are: H0: the population medians are all equal H1: the medians are not all equal Why should I use a Kruskal-Wallis test? Example. A type of fertilizer in 5 different concentrations and agricultural plot size of 30 tested. The yield obtained from each plot was reported in the following table. Weather conditions are the same plots. Table1 the resulting product is an agricultural plot of 30 in 5 different concentrations Fifth concentration The product obtained (in tonnes) Fourth concentration Third concentration Second concentration First concentration (With Minitab) 1

2 Shape1 How to insert the data of 30 agricultural plots in 5 different concentrations Analyze Nonparametric Tests Legacy Dialogs K Independent Samples Shape2 Kruskal-Wallis nonparametric test to examine the assumption of the equality of the average yields of 30 plots in 5 levels Table2 Ranked by means of the nonparametric test for equality 30 plots in 5 levels Crop Ranks ChemicalC N Mean Rank Total 36 2

3 Table3 Kruskal-Wallis nonparametric test results mean equality hypothesis product value 30 plots in 5 levels Test Statistics a,b Crop Chi-Square df 4 Asymp. Sig..000 a. Kruskal Wallis Test b. Grouping Variable: ChemicalC Ranks average concentration of 4, 1, 5, 3 and 2 is the highest. C h i sq u a re & P value Thus, the alternative hypothesis that means there is a significant difference in the plots with different concentrations of the product obtained, will be accepted. The different concentrations of fertilizer can be effective in the harvest. The Kruskal-Wallis nonparametric test track to obtain more information Analyze Nonparametric Tests Independent Samples Shape3 How do Kruskal-Wallis test to check the assumption of the equality of the average yields of 30 plots in 5 levels The box plot results of concentrations and the results of two different concentrations with each other. It was the same thing that the topic of analysis of variance and Post Hoc tests mentioned. Shape4 Kruskal-Wallis test to check the assumption of the equality of the average yields of 30 plots in 5 levels 3

4 Shape5 Box plot 30 plots average yield on 5 levels Table4 Kruskal-Wallis test to test the equality assuming an average yield of 30 plots in 5 levels Shape6 Kruskal-Wallis test to check the graph of the average parity assumed the 30 plots in 5 levels 4

5 Table5 Kruskal-Wallis nonparametric test pairwise comparison test References 1. Abolfazl Ghoodjani. (2016), Slash and Skew Slash Distribution. 2. Abolfazl Ghoodjani. (2016), Fertility Rate and Economic Development, Long-term 60-year Trend of Iran. 3. Abolfazl Ghoodjani. (2016), Advanced Statistical Methods and Applications. 4. Abolfazl Ghoodjani. (2016), Workshop SPSS-ISERB Abolfazl Ghoodjani. (2016), Time Series Analysis: Fertility Rate & Economic Development. 6. Abolfazl Ghoodjani. (2016), Economic Participation Rate In Iran. 5