Mann-Kendall + Sen’s Slope
Mann-Kendall + Sen’s Slope is one of the statistical analyses applied automatically in MerQur. This page illustrates — on a Education Sciences 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?
Mann-Kendall + Sen’s Slope automatically applies 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 and chart. Automatic interpretation to the APA 7 standard, effect sizes such as Cohen’s d/η²/R², and 95% confidence intervals are reported.
📌 When is it used?
- Statistical analysis of measurements in the Education Sciences 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 Mann-Kendall + Sen’s Slope.
Panel assignments (form fields in the program):
- Value Column:
ulusal_okuma_puan - date_col:
yil - time_unit:
year
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 — Education Sciences
ℹ Note: The scenario, MerQur output and interpretation below were produced by actually running the real example dataset in MerQur. Numeric results on your own data will differ; the goal is to show how the analysis is set up and interpreted end-to-end.
🎬 Example File
This analysis is demonstrated on the following example dataset for Education Sciences:
Egitim_Bilimleri/98_mann_kendall_reading_trend.xlsx
🎬 Scenario
Let’s say we want to know whether national reading achievement has genuinely improved over the last four decades. We have 40 yearly observations, each with a year and the national_reading_score for that year. Rather than assume a straight-line trend, we want a robust, distribution-free test of whether there is a monotonic upward or downward tendency, plus an estimate of the rate of change. We use the Mann-Kendall trend test together with Sen’s slope, because they detect and quantify a monotonic trend in the reading scores without requiring the data to be normally distributed.
⚙️ Variable Selection
- Time (ordering): year
- Series (value): national_reading_score
Data Preview (First 5 Rows)
| year | national_reading_score |
|---|---|
| 1985.0 | 396.9 |
| 1986.0 | 386.9 |
| 1987.0 | 396.7 |
| 1988.0 | 395.9 |
| 1989.0 | 380.8 |
n = 40 · Columns: year, national_reading_score
📈 MerQur Output
💬 Interpretation
We tested whether national reading scores show a significant long-term trend with the Mann-Kendall test — a nonparametric, outlier- and distribution-robust trend test. The result is highly significant (p < .001) and the direction is increasing: reading achievement is rising consistently over the years. This may reflect the positive cumulative effect of educational policies/interventions. Mann-Kendall + Sen’s slope is the gold standard for long-term trend detection — from climate to economy, from education to health; Sen’s slope gives the trend magnitude without being affected by outliers.
⚠ 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 Education Sciences file.
▶ Mann-Kendall + Sen’s Slope — video walkthrough
This section is part of the Zaman Serisi Analizi video (6 analyses in one video). The link below jumps straight to 6:54, where this analysis begins. Narration is in Turkish.
🧪 Natural Sciences & Mathematics · 🏛 Architecture, Planning & Design · ⚙ Engineering · 🏥 Health Sciences · 📊 Social, Humanities & Admin Sciences · 🏃 Sport Sciences · 🌾 Agriculture, Forestry & Aquatic
📚 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.