Korelasyon (Pearson / Spearman / Kendall)
Correlation (Pearson / Spearman / Kendall) is one of the statistical analyses automatically performed in MerQur. This page illustratively demonstrates how the analysis is applied to a sample dataset from the field of Agriculture, Forestry & Fisheries, how the MerQur output appears, and how it is reported in APA 7 format.
🎯 What is it for?
Correlation (Pearson / Spearman / Kendall) automatically performs in the background all the assumption checks required for the relevant data type (normality, homogeneity of variance, etc.) and presents the results with 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 Correlation (Pearson / Spearman / Kendall).
Panel assignments (form fields in the program):
- Columns:
[agac_id, yas_yil, dbh_cm, +3 daha] - method:
pearson
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 using the following sample file for the Agriculture, Forestry and Aquaculture field:
MerQur_Hoca_Tanitim/Ziraat_Orman_Su/33_korelasyon_orman_olcumler.xlsx
Data Preview (First 5 Rows)
| parsel_id | sulama_mm | gubre_kg_da | sicaklik_C | nem_pct | verim_kg_da |
|---|---|---|---|---|---|
| 1.00 | 30.20 | 105.80 | 20.20 | 51.80 | 215.50 |
| 2.00 | 201.00 | 170.40 | 15.70 | 65.60 | 380.40 |
| 3.00 | 241.50 | 37.40 | 28.90 | 89.60 | 211.90 |
| 4.00 | 64.00 | 197.20 | 20.10 | 87.00 | 417.20 |
| 5.00 | 210.90 | 172.00 | 17.00 | 45.40 | 378.30 |
n = 180 · Sütunlar: parsel_id, sulama_mm, gubre_kg_da, sicaklik_C, nem_pct, verim_kg_da
MerQur Output (Illustrative)
MerQur Interpretation (Plain Language)
A positive, moderate-to-strong relationship was found between parsel_id and sulama_mm (r = .65, p < .001). An increase in one variable is observed together with an increase in the other.
APA 7 Interpretation (Academic Format · Illustrative)
parsel_id and sulama_mm variables, r(178) = .65, p < .001. The coefficient of determination (r² = .42) indicates that approximately 42% of the variance in the sulama_mm variable is explained by parsel_id.⚠ 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.
🎓 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.