Kruskal-Wallis Test

🌾 Agriculture, Forestry & Aquatic · Kruskal-Wallis Test

Kruskal-Wallis Test

Non-parametrik · ANOVA Karşılığı
🆕 New in v1.0.5: A Chart tab was added to this analysis (boxplot, interaction, profile, bar, scatter, biplot, or forecast — depending on analysis type).

Kruskal-Wallis Test is one of the statistical analyses applied automatically in MerQur. This page illustrates — on a Agriculture, Forestry & Aquatic sample dataset — how the analysis is run, what the MerQur output looks like, and how the result is reported in APA 7 format.

🎯 What is it for?

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

📌 When is it used?

  • Statistical analysis of measurements in the Agriculture, Forestry & Aquatic domain
  • To produce APA 7-compatible result tables for academic publications
  • Hypothesis testing and decision-making processes
  • Undergraduate / master’s / PhD theses after the appropriate method has been selected

📐 Assumptions

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

If assumptions are violated, MerQur automatically suggests a non-parametric or robust alternative.

🛠 How to do it in MerQur

1

Load the data. Select the sample file from File → Open. MerQur auto-detects column types.

2

Select the analysis. From the left side select Kruskal-Wallis Test.

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

▶ Run — click the button. Results are produced automatically as a table + chart.

6

📄 Export to Word. APA 7-formatted report with italic statistical symbols.

📊 Sample Dataset — Agriculture, Forestry & Aquatic

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

🎬 File Used in the Video

The YouTube video for this page was recorded for the Agriculture, Forestry & Aquatic domain using the sample file below:

MerQur_Hoca_Tanitim/Ziraat_Orman_Su/16_kruskal_wallis_toprak_gelisim.xlsx

Topic: Kruskal-Wallis Test analysis applied to a real Agriculture, Forestry & Aquatic sample dataset.

Data Preview (First 5 Rows)

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

n = 45 · Columns: parsel_id, toprak, verim_ton_ha

MerQur Output (Illustrative)

ANOVA TABLOSU (Kruskal-Wallis Test) ───────────────────────────────────────────── Kaynak SS df F p η²p toprak 542.30 2 24.82 <.001 .312 Hata 1184.50 42 POST-HOC (Tukey HSD) ───────────────────────────────────────────── Anlamlı ikili karşılaştırmalar a/b/c gruplaması ile raporlanır.

MerQur Narrative Interpretation

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

APA 7 Interpretation (Academic Format · Illustrative)

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

⚠ Common Mistakes

  • Misidentifying the data type (e.g., loading a categorical variable as numeric)
  • Skipping assumption checks and going straight to the p-value
  • Failing to report effect size — APA 7 requires both p and effect size
  • Failing to apply a Type I error correction (Bonferroni/Tukey) in multiple comparisons
  • Not switching to a non-parametric alternative when n is insufficient

📹 Video Walkthrough

Watch the video below for an end-to-end walkthrough of this analysis on a Agriculture, Forestry & Aquatic file.

▶

The video will be uploaded to the MerQur YouTube channel soon

📺 MerQur YouTube Channel

📚 If You Used This Analysis, Cite MerQur

If you performed this analysis using MerQur in a scientific study, please use the citation below as part of your academic citation obligations (APA 7):

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

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

Sources:
  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.