UMAP
UMAP 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?
UMAP, 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 UMAP.
Variable assignments.
- Variable 1:
alt_tip - Variable 2:
feat_01
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:
72_UMAP / Ziraat_Orman_Muhendislik__72_umap_5tip.xlsx
Data Preview (First 5 Rows)
| ornek_id | alt_tip | feat_01 | feat_02 | feat_03 | feat_04 | feat_05 | feat_06 | feat_07 | feat_08 | feat_09 | feat_10 | feat_11 | feat_12 | feat_13 | feat_14 | feat_15 | feat_16 | feat_17 | feat_18 | feat_19 | feat_20 | feat_21 | feat_22 | feat_23 | feat_24 | feat_25 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | S1 | 0.63 | -1.00 | -0.79 | -0.17 | 0.25 | 0.23 | -2.22 | 1.06 | -0.37 | -1.15 | -1.71 | -1.08 | 1.58 | -2.02 | 0.31 | 0.90 | -1.34 | -1.58 | 0.31 | 0.04 | -0.17 | -0.98 | -1.09 | -1.28 | -1.63 |
| 2 | S1 | 0.65 | -0.76 | -0.26 | 3.02 | -1.03 | -0.21 | 1.30 | 0.07 | -0.41 | 0.04 | 0.30 | -1.16 | 1.15 | 0.59 | 1.69 | -0.18 | 0.23 | 1.26 | 1.33 | 1.15 | 0.11 | 0.11 | 0.03 | -1.71 | -1.70 |
| 3 | S1 | 0.26 | 0.79 | 0.37 | 0.30 | -0.75 | 0.57 | -0.97 | -0.03 | -0.36 | 0.09 | 0.71 | 1.89 | -0.31 | 1.03 | 0.39 | 0.22 | -0.21 | 0.40 | -0.53 | 0.73 | -0.01 | -1.06 | -0.76 | -1.42 | -0.78 |
| 4 | S1 | 1.74 | -0.82 | 0.09 | 0.18 | 1.02 | 0.03 | -2.52 | 0.60 | -0.64 | 0.06 | -0.15 | 2.11 | -0.15 | 2.39 | -0.85 | 1.95 | -0.64 | 0.02 | -0.97 | 0.45 | -1.92 | 0.63 | -0.57 | 0.73 | -0.54 |
| 5 | S1 | -1.53 | -0.93 | 0.25 | 1.78 | -0.17 | -0.04 | 0.39 | 0.27 | -1.43 | 0.92 | 0.72 | 1.17 | 0.26 | -0.43 | 0.27 | -0.17 | -1.94 | -0.95 | -1.90 | 0.68 | -0.68 | -1.77 | -1.01 | 0.69 | 1.00 |
n = 200 · Columns: ornek_id, alt_tip, feat_01, feat_02, feat_03, feat_04, feat_05, feat_06, feat_07, feat_08, feat_09, feat_10, feat_11, feat_12, feat_13, feat_14, feat_15, feat_16, feat_17, feat_18, feat_19, feat_20, feat_21, feat_22, feat_23, feat_24, feat_25
MerQur Output (Illustrative)
MerQur Narrative Interpretation
UMAP 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)
alt_tip 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.
▶ UMAP — video walkthrough
This section is part of the Kümeleme ve Boyut İndirgeme video (7 analyses in one video). The link below jumps straight to 10:43, 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.