Cross-Tabulation Analysis

Kategorik · Betimsel

🆕 New in v1.0.5: A Chart tab was added to this analysis (boxplot, interaction, profile, bar, scatter, biplot, or forecast — depending on analysis type).

Cross-Tabulation Analysis is one of the statistical analyses applied automatically in MerQur. This page illustrates — on a Sport 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?

Cross-Tabulation Analysis automatically performs all required assumption checks (normality, homogeneity of variance, etc.) for the relevant data type in the background 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?

Statistical analysis of measurements in the Sport 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 Cross-Tabulation Analysis.

Panel assignments (form fields in the program):

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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 — Sport 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 Sport Sciences:

Spor_Bilimleri/28_cross_age_motivation.xlsx

🎬 Scenario

We examine age group and motivation in a cross-tab. For the relationship of two qualitative variables, cross-tab is appropriate.

⚙️ Variable Selection

Variables: age_group
Variables: motivation

Data Preview (First 5 Rows)

athlete_id	age_group	motivation
1	26-35	winning
2	>35	social
3	18-25	entertainment
4	18-25	health
5	26-35	health

n = 350 · Columns: athlete_id, age_group, motivation

📈 MerQur Output

CROSS-TABULATION ANALYSIS RESULT ───────────────────────────────────────────── chi^2(6) = 27.24 p < .001 *** Cramer’s V = 0.197 (Moderate) H0 REJECTED

💬 Interpretation

We examined two categorical variables (age group x motivation) in a cross-tab: chi^2(6) = 27.24, p < .001, V = 0.20 — a significant, moderate relationship. Cross-tab + chi-square shows the direction and strength of the association between two qualitative variables at the cell level. In sports science it is used to describe age-motivation, demography-attitude relationships; Cramer’s V (0.20) measures the practical strength.

⚠ 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 Sport Sciences file.

▶ Cross-Tabulation Analysis — video walkthrough

This section is part of the Kategorik Veri Analizleri video (8 analyses in one video). The link below jumps straight to 11:28, where this analysis begins. Narration is in Turkish.

▶ Watch this analysis (11:28) 📺 All videos

🔀 The same analysis in other disciplines:
🎓 Education Sciences · 🧪 Natural Sciences & Mathematics · 🏛 Architecture, Planning & Design · ⚙ Engineering · 🏥 Health Sciences · 📊 Social, Humanities & Admin 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 →

Sources:

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.