VARCLUS (Variable Clustering)
VARCLUS (Variable Clustering) 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?
VARCLUS (Variable Clustering), 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 VARCLUS (Variable Clustering).
Variable assignments.
- Variable 1:
toprak_m1 - Variable 2:
toprak_m2
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:
38_VARCLUS_Değişken_Kümeleme / Ziraat_Orman_Muhendislik__38_varclus_18madde.xlsx
Data Preview (First 5 Rows)
| parsel_id | toprak_m1 | toprak_m2 | toprak_m3 | toprak_m4 | toprak_m5 | toprak_m6 | iklim_m1 | iklim_m2 | iklim_m3 | iklim_m4 | iklim_m5 | iklim_m6 | genetik_m1 | genetik_m2 | genetik_m3 | genetik_m4 | genetik_m5 | genetik_m6 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1.00 | -0.99 | -1.85 | -1.48 | -1.91 | -1.46 | -1.48 | -0.43 | -1.10 | -0.75 | -0.62 | -0.71 | -1.49 | -1.50 | -1.00 | -1.69 | -1.30 | -1.94 | -1.72 |
| 2.00 | -1.18 | -1.39 | -1.21 | -1.68 | -1.22 | -1.90 | 0.92 | 0.41 | 0.33 | 0.67 | 1.15 | 0.15 | -0.61 | -0.86 | -0.22 | -0.38 | -0.33 | -0.13 |
| 3.00 | -0.03 | 0.19 | 0.56 | 0.10 | 0.45 | 1.16 | -1.66 | -2.07 | -0.93 | -1.47 | -1.15 | -1.64 | -0.14 | 0.85 | -0.33 | 0.95 | 1.25 | 0.68 |
| 4.00 | -0.88 | -0.52 | -0.94 | -0.63 | -1.23 | -1.02 | 0.38 | 0.13 | 0.14 | 0.17 | 0.87 | -0.27 | 1.32 | 1.51 | 0.99 | 1.08 | 1.69 | 1.38 |
| 5.00 | -0.32 | -0.92 | -0.68 | -0.47 | -0.78 | -0.81 | -1.20 | -2.38 | -1.09 | -1.30 | -1.45 | -0.89 | -1.63 | -1.22 | -1.28 | -1.49 | -0.47 | -2.06 |
n = 180 · Columns: parsel_id, toprak_m1, toprak_m2, toprak_m3, toprak_m4, toprak_m5, toprak_m6, iklim_m1, iklim_m2, iklim_m3, iklim_m4, iklim_m5, iklim_m6, genetik_m1, genetik_m2, genetik_m3, genetik_m4, genetik_m5, genetik_m6
MerQur Output (Illustrative)
MerQur Narrative Interpretation
VARCLUS (Variable Clustering) revealed a statistically significant finding among the variables (p < .001). Detailed results and visualizations are produced automatically in the MerQur output panel.
APA 7 Interpretation (Academic Format · Illustrative)
toprak_m1 showed a statistically significant effect/association (p < .001). The effect size was medium-to-large, suggesting the finding has practical importance. For the detailed report, use MerQur’s APA 7 Word export.⚠ 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.
▶ VARCLUS (Variable Clustering) — video walkthrough
This section is part of the İlişki ve Korelasyon video (6 analyses in one video). The link below jumps straight to 9:30, where this analysis begins. Narration is in Turkish.
🎓 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 →
- 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.