Hiyerarşik Kümeleme
Hierarchical Clustering is one of the statistical analyses applied automatically in MerQur. This page provides a representative illustration of how the analysis is applied to a sample dataset from the fields of Agriculture, Forestry, and Aquaculture, how the MerQur output will appear, and how it will be reported in APA 7 format.
🎯 What is it for?
Hierarchical Clustering automatically performs all necessary assumption checks (normality, homogeneity of variance, etc.) in the background for the relevant data type and presents the results in a clear table + 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?
- 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
Load the data. Select the sample file from the File → Open menu. MerQur automatically detects column types.
Select the analysis. From the left sidebar, select Hierarchical Clustering.
Panel assignments (form fields in the program):
- Columns:
[ornek_id, protein_1, protein_2, +8 daha] - Number of clusters:
4 - Linkage:
ward - Missing strategy:
drop
Optional settings. Effect size ✓ · 95% confidence interval ✓ · Assumption checks (automatic).
Press the ▶ Run button. Results are generated automatically as a table + chart.
📄 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 for the Agriculture, Forestry and Aquaculture field using the sample file below:
MerQur_Hoca_Tanitim/Ziraat_Orman_Su/67_hiyerarsik_tur_protein_profili.xlsx
Data Preview (First 5 Rows)
| ornek_id | tur | feat_01 | feat_02 | feat_03 | feat_04 | feat_05 | feat_06 | feat_07 | feat_08 | feat_09 | feat_10 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | A | 2.18 | 1.90 | 0.31 | -1.57 | -0.52 | -0.19 | -0.15 | -0.38 | 0.97 | 1.81 |
| 2 | A | 1.29 | 1.98 | 2.07 | -1.31 | 1.40 | -1.91 | -0.22 | -0.53 | 0.46 | 0.98 |
| 3 | A | -0.62 | 1.83 | 1.52 | 0.54 | -0.34 | 2.51 | 1.93 | 0.49 | -0.11 | -0.71 |
| 4 | A | -1.44 | -0.46 | 0 | 0.12 | 0.46 | -0.58 | 1.94 | -2.00 | 0.55 | -1.09 |
| 5 | A | -0.16 | -0.20 | 0.31 | 1.56 | -0.68 | 0.39 | -1.45 | -1.70 | 1.02 | 2.05 |
n = 40 · Sütunlar: ornek_id, tur, feat_01, feat_02, feat_03, feat_04, feat_05, feat_06, feat_07, feat_08, feat_09, feat_10
MerQur Output (Illustrative)
MerQur Interpretation (Plain Language)
Hierarchical Clustering revealed a statistically significant finding among the relevant variables (p < .001). Detailed results and visuals are generated automatically in MerQur’s output panel.
APA 7 Interpretation (Academic Format · Illustrative)
tur (p < .001). The effect size was at a medium-large level, indicating that the findings carry practical significance. For a detailed report, MerQur’s APA 7 Word output can be used.⚠ 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 on the Agriculture, Forestry and Aquaculture file.
🎓 Educational Sciences · 🧪 Natural Sciences and Mathematics · 🏛 Architecture, Planning and Design · ⚙ Engineering · 🏥 Health Sciences · 📊 Social, Humanities and Administrative Sciences · 🏃 Sport Sciences
📚 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 →
- 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.