Kruskal-Wallis Testi

🌾 Ziraat, Orman ve Su Ürünleri · Kruskal-Wallis Testi

Kruskal-Wallis Testi

Non-parametrik · ANOVA Karşılığı
🆕 v1.0.5’te yeni: Bu analize Grafik sekmesi eklendi (analiz tipine göre boxplot, etkileşim, profil, çubuk, saçılım, biplot veya tahmin grafiği).

The Kruskal-Wallis Test is one of the statistical analyses automatically performed in MerQur. This page illustratively demonstrates, using a sample dataset from the field of Agriculture, Forestry and Aquaculture, how the analysis is applied, how the MerQur output appears, and how it is reported in APA 7 format.

🎯 What is it for?

The Kruskal-Wallis Test automatically performs all necessary assumption checks (normality, homogeneity of variance, etc.) for the relevant data type in the background and presents the results with a clear table + chart. Automatic interpretation to the APA 7 standard, effect sizes such as Cohen’s d/η²/R², and 95% confidence intervals are reported.

📌 When is it used?

  • In the statistical analysis of measurements belonging to the Agriculture, Forestry and Aquaculture field
  • To produce APA 7 compliant result tables for academic publication
  • In hypothesis testing and decision-making processes
  • After selecting an appropriate method in undergraduate / master’s / doctoral theses

📐 Assumptions

  • Appropriate scale — Variables must be at the scale level required by the analysis (nominal/ordinal/interval/ratio)
  • Independent observations — Observations must come from mutually independent individuals
  • Adequate sample — The minimum n requirement for the analysis must be met
  • Outlier check — Outliers must be detected and evaluated

If the assumptions are violated, MerQur automatically steers you toward a non-parametric or robust alternative.

🛠 How to do it in MerQur

1

Load the data. Select the sample file from the File → Open menu. MerQur automatically detects column types.

2

Select the analysis. Choose Kruskal-Wallis Test from the left sidebar.

3

Panel assignments (form fields in the program):

  • Group Column: toprak_tipi
  • Value Column: yillik_gelisim_cm
4

Optional settings. Effect size ✓ · 95% confidence interval ✓ · Assumption checks (automatic).

5

Press the ▶ Run button. Results are generated automatically as a table + chart.

6

📄 Export to Word. A report in APA 7 format with italic statistical symbols.

📊 Sample Dataset — Ziraat, Orman ve Su Ürünleri

ℹ Note: The MerQur output and interpretation tables on this page are illustrative and intended to help understand the analysis. The numerical results for your own data may differ; this page does not have to match the YouTube video walkthrough exactly.

🎬 Example File Used in the Video

The YouTube video walkthrough of this page was recorded using the sample file below for the Agriculture, Forestry and Aquaculture field:

MerQur_Hoca_Tanitim/Ziraat_Orman_Su/16_kruskal_wallis_toprak_gelisim.xlsx

Topic: Application of the Kruskal-Wallis Test analysis on a real sample data set belonging to the Agriculture, Forestry and Aquaculture field.

Data Preview (First 5 Rows)

parsel_idtoprakverim_ton_ha
1Kil5.50
2Kil5.30
3Kil1.46
4Kil3.04
5Kil3.20

n = 45 · Sütunlar: parsel_id, toprak, verim_ton_ha

MerQur Output (Illustrative)

ANOVA TABLE (Kruskal-Wallis Test) ───────────────────────────────────────────── Source SS df F p η²p toprak 542.30 2 24.82 <.001 .312 Error 1184.50 42 POST-HOC (Tukey HSD) ───────────────────────────────────────────── Significant pairwise comparisons are reported using a/b/c grouping.

MerQur Interpretation (Plain Language)

The Kruskal-Wallis Test showed that the effect of the toprak levels on verim_ton_ha is significant (p < .001, η²p = .31, medium-to-large effect). Tukey HSD post-hoc comparisons determine between which groups a significant difference exists.

APA 7 Interpretation (Academic Format · Illustrative)

According to the Kruskal-Wallis Test results, the toprak variable has a significant effect on verim_ton_ha, F(2, 42) = 24.82, p < .001, η²p = .31. The effect size is at a medium-to-large level according to Cohen’s (1988) criteria. Tukey HSD post-hoc comparisons revealed the significant differences between the groups.

⚠ Common Mistakes

  • Specifying the data type incorrectly (e.g., loading a categorical variable as numeric)
  • Skipping the assumption checks and looking directly at the p-value
  • Not reporting the effect size — APA 7 requires both p and the effect size
  • Not applying a Type I error correction (Bonferroni/Tukey) in multiple comparisons
  • Not switching to a non-parametric alternative when n is insufficient

📹 Video Walkthrough

You can watch the video below for an end-to-end application of this analysis using the Agriculture, Forestry and Aquaculture file.

▶

The video will soon be uploaded to the MerQur YouTube channel

📺 MerQur YouTube Channel

📚 If You Used This Analysis, Cite MerQur

If you performed this analysis in a scientific study using MerQur, please use the following citation (APA 7) in accordance with the academic citation requirement:

Örücü, Ö. K. (2026). MerQur: An Integrated Academic Data Analysis and Reporting Platform [Computer Software] (Version 1.0.0). https://doi.org/10.53463/merqur.2026001

For BibTeX, RIS, EndNote and the English equivalent: all citation formats →

References:
  1. American Psychological Association. (2020). Publication manual of the American Psychological Association (7th ed.).
  2. Field, A. (2018). Discovering statistics using IBM SPSS Statistics (5th ed.). Sage.
  3. Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Lawrence Erlbaum.