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Sample study · comparative design
Anxiety Before and After a Programme
Research information
Statement of the problem
This study examines whether a stress-management programme changes participants' anxiety, comparing each participant's pre-test and post-test scores.
Objectives
- To describe the anxiety_score of the participants.
- To determine whether anxiety_score differs across phase (the pre-test and post-test).
Dataset
pre_post.csv64 rows × 3 cols
| Column | Kind | Missing | Distinct |
|---|---|---|---|
| participant | categorical | 0 | 32 |
| phase | categorical | 0 | 2 |
| anxiety_score | numeric | 0 | 63 |
Feasibility & estimateFree
✓ Feasibledesign: comparative · via heuristic
Detected a comparative design with 2 analyzable variable(s) and 2 analytical question(s). Recommended 2 statistical test(s). Estimated cost: 29 credits.
Recommended analysis
To describe the anxiety_score of the participants.
Descriptive Statistics(anxiety_score)
To determine whether anxiety_score differs across phase (the pre-test and post-test).
Paired-Samples t-Test(anxiety_score, phase)
Dataset Complexity8
Statistical Tests6
AI Interpretation6
Visualizations4
Report Generation5
Total to run29 credits
Estimated runtime: ~40-80 seconds
ResultsComputed
2 tests29 credits
Descriptive Statistics (anxiety_score)
| n | max | min | std | mean | mode | range | median | variable | variance |
|---|---|---|---|---|---|---|---|---|---|
| 64 | 65.700 | 29.700 | 8.355 | 46.938 | 34.900 | 36 | 47.700 | anxiety_score | 69.804 |
Paired-Samples t-Test (anxiety_score, phase)
significantt-11.72df31p< .001
Cohen's d-2.072
large
| n | std | mean | group |
|---|---|---|---|
| 32 | 7.511 | 42.472 | post-test |
| 32 | 6.654 | 51.403 | pre-test |
The result is statistically significant (p = 0.0000 < 0.05).
Report
Publication-ready report
Tests used · Results · Discussion — generated from the computed statistics.
Numeric-claim check passed · 14 numbers verified · prose: llm:gemini
Reproducible code
Download the exact Jupyter notebook or Python script that reproduces these results with widely-used libraries (scipy, statsmodels, lifelines).
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