Canonical Correlation (CCA)
Canonical Correlation (CCA) 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?
Canonical Correlation (CCA), 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 Canonical Correlation (CCA).
Variable assignments.
- Variable 1:
DBH - Variable 2:
boy_m
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:
36_Kanonik_Korelasyon_CCA / Ziraat_Orman_Muhendislik__36_cca_fizik_biyo.xlsx
Data Preview (First 5 Rows)
| agac_id | DBH | boy_m | yas | tac_cap | kabuk_kalın | biyokutle | yaprak_alan | klorofil | saglik_skor |
|---|---|---|---|---|---|---|---|---|---|
| 1.00 | 21.30 | 15.00 | 23.00 | 10.00 | 2.20 | 251.00 | 84.20 | 52.61 | 4.38 |
| 2.00 | 25.10 | 17.60 | 34.00 | 7.60 | 2.62 | 201.00 | 90.90 | 43.54 | 3.70 |
| 3.00 | 25.50 | 19.80 | 93.00 | 8.10 | 2.50 | 157.00 | 80.80 | 27.64 | 1.94 |
| 4.00 | 23.50 | 24.30 | 42.00 | 9.90 | 1.96 | 178.00 | 76.60 | 38.30 | 3.96 |
| 5.00 | 17.30 | 20.50 | 39.00 | 7.50 | 1.65 | 210.00 | 76.40 | 43.87 | 3.47 |
n = 150 · Columns: agac_id, DBH, boy_m, yas, tac_cap, kabuk_kalın, biyokutle, yaprak_alan, klorofil, saglik_skor
MerQur Output (Illustrative)
MerQur Narrative Interpretation
Canonical Correlation (CCA) 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)
DBH 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.
▶ Canonical Correlation (CCA) — video walkthrough
This section is part of the İlişki ve Korelasyon video (6 analyses in one video). The link below jumps straight to 5:46, 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.