Mann-Whitney U Test

Non-parametrik · Karşılaştırma

Mann-Whitney U 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?

Mann-Whitney U Test, ilgili veri türü için gerekli tüm varsayım kontrollerini (normallik, varyans homojenliği, vb.) arka planda otomatik uygular ve sonuçları açık bir tablo + grafik ile sunar. APA 7 standardında otomatik yorumlama, Cohen’s d/η²/R² gibi etki büyüklükleri ve %95 güven aralıkları raporlanır.

📌 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

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

Select the analysis. From the left side select Mann-Whitney U Test.

Variable assignments.

Variable 1: tarım_tipi
Variable 2: kalite_puan

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

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

📄 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:

14_Mann_Whitney_U_Testi / Ziraat_Orman_Muhendislik__14_mann_whitney_tarim_kalite.xlsx

Topic: Mann-Whitney U Test analysis applied to a real Agriculture, Forestry & Aquatic sample dataset.

Data Preview (First 5 Rows)

parsel_id	tarım_tipi	kalite_puan
3	Organik	6
35	Organik	7
40	Organik	5
70	Konvansiyonel	5
63	Konvansiyonel	4

n = 85 · Columns: parsel_id, tarım_tipi, kalite_puan

MerQur Output (Illustrative)

BETİMSEL İSTATİSTİKLER ───────────────────────────────────────────── Grup n Ortalama SS SH Organik 42 14.83 2.45 0.32 Konvansiyonel 43 11.21 2.78 0.37 NORMALLİK (Shapiro-Wilk) ───────────────────────────────────────────── Organik : W = 0.974, p = .312 ✓ Konvansiyonel: W = 0.968, p = .241 ✓ LEVENE (Varyans Homojenliği) ───────────────────────────────────────────── F = 1.12, p = .291 ✓ (homojen) MANN-WHITNEY U TEST RESULT ───────────────────────────────────────────── t(83) = 7.24, p < .001 Ortalama farkı = 3.62 %95 GA: [2.64, 4.60] Cohen’s d = 1.38 (büyük etki)

MerQur Narrative Interpretation

Organik grubu (n=42, ortalama=14.83) Konvansiyonel grubuna (n=43, ortalama=11.21) kıyasla daha yüksek kalite_puan değeri göstermiştir. Aradaki fark istatistiksel olarak anlamlıdır (p < .001). Cohen’s d = 1.38 büyük etki düzeyini işaret eder.

APA 7 Interpretation (Academic Format · Illustrative)

Bağımsız örneklem t-testi, Organik grubunun (M = 14.83, SD = 2.45) Konvansiyonel grubuna (M = 11.21, SD = 2.78) kıyasla anlamlı düzeyde daha yüksek kalite_puan değeri gösterdiğini ortaya koymuştur, t(83) = 7.24, p < .001, Cohen’s d = 1.38. Ortalama farkı 3.62 birim olup %95 güven aralığı [2.64, 4.60] sınırları arasındadır. Etki büyüklüğü Cohen (1988) ölçütlerine göre büyük etki düzeyindedir.

⚠ 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.

▶ Mann-Whitney U Test — video walkthrough

This section is part of the Non-Parametrik Testler video (7 analyses in one video). The link below jumps straight to 0:00, where this analysis begins. Narration is in Turkish.

▶ Watch this analysis (0:00) 📺 All videos

🔀 The same analysis in other disciplines:
🎓 Education Sciences · 🧪 Natural Sciences & Mathematics · 🏛 Architecture, Planning & Design · ⚙ Engineering · 🏥 Health Sciences · 📊 Social, Humanities & Admin Sciences · 🏃 Sport Sciences

📚 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:

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