Read-only sample study. A complete walkthrough — from problem statement to a validated report — using wine.csv (178 rows × 13 cols). Sign in to run your own.
Sample study · correlational design
Wine Chemical Profile
Research information
Statement of the problem
This study explores the chemical composition of wines and the latent structure underlying the measured constituents.
Objectives
- To describe the alcohol, total_phenols, flavanoids, and color_intensity of the wines.
- To determine the relationship between total_phenols and flavanoids.
- To uncover the underlying factor structure among total_phenols, flavanoids, nonflavanoid_phenols, proanthocyanins, and hue.
Dataset
wine.csv178 rows × 13 cols
| Column | Kind | Missing | Distinct |
|---|---|---|---|
| alcohol | numeric | 0 | 126 |
| malic_acid | numeric | 0 | 133 |
| ash | numeric | 0 | 79 |
| alcalinity_of_ash | numeric | 0 | 63 |
| magnesium | numeric | 0 | 53 |
| total_phenols | numeric | 0 | 97 |
| flavanoids | numeric | 0 | 132 |
| nonflavanoid_phenols | numeric | 0 | 39 |
| proanthocyanins | numeric | 0 | 101 |
| color_intensity | numeric | 0 | 132 |
| hue | numeric | 0 | 78 |
| od280/od315_of_diluted_wines | numeric | 0 | 122 |
| proline | numeric | 0 | 121 |
Feasibility & estimateFree
✓ Feasibledesign: correlational · via heuristic
Detected a correlational design with 13 analyzable variable(s) and 3 analytical question(s). Recommended 3 statistical test(s). Estimated cost: 52 credits.
Recommended analysis
To describe the alcohol, total_phenols, flavanoids, and color_intensity of the wines.
Descriptive Statistics(alcohol, total_phenols, flavanoids, color_intensity)
To determine the relationship between total_phenols and flavanoids.
Pearson Correlation(total_phenols, flavanoids)
To uncover the underlying factor structure among total_phenols, flavanoids, nonflavanoid_phenols, proanthocyanins, and hue.
Exploratory Factor Analysis(total_phenols, flavanoids, nonflavanoid_phenols, proanthocyanins, hue)
Dataset Complexity18
Statistical Tests14
AI Interpretation9
Visualizations6
Report Generation5
Total to run52 credits
Estimated runtime: ~45-90 seconds
ResultsComputed
3 tests52 credits
Descriptive Statistics (alcohol, total_phenols, flavanoids, color_intensity)
| n | max | min | std | mean | mode | range | median | variable | variance |
|---|---|---|---|---|---|---|---|---|---|
| 178 | 14.830 | 11.030 | 0.812 | 13.001 | 12.370 | 3.800 | 13.050 | alcohol | 0.659 |
| 178 | 3.880 | 0.980 | 0.626 | 2.295 | 2.200 | 2.900 | 2.355 | total_phenols | 0.392 |
| 178 | 5.080 | 0.340 | 0.999 | 2.029 | 2.650 | 4.740 | 2.135 | flavanoids | 0.998 |
| 178 | 13 | 1.280 | 2.318 | 5.058 | 2.600 | 11.720 | 4.690 | color_intensity | 5.374 |
Spearman Rank Correlation (total_phenols, flavanoids)
significantr.879R².773N178p< .001
Spearman r0.879
large
The result is statistically significant (p = 0.0000 < 0.05).
Spearman Rank Correlation was used instead of the Pearson Correlation because the latter's assumption(s) were not met (Normality of total_phenols (Shapiro-Wilk), Normality of flavanoids (Shapiro-Wilk)).
Exploratory Factor Analysis (total_phenols, flavanoids, nonflavanoid_phenols, proanthocyanins, hue)
KMO.764N178
| item | factor 1 |
|---|---|
| total_phenols | -0.873 |
| flavanoids | -1.000 |
| nonflavanoid_phenols | 0.531 |
| proanthocyanins | -0.665 |
| hue | -0.506 |
Extracted 1 factor(s) (Kaiser criterion); 54.9% variance explained.
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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