Art of Stat
Art of Stat Summary
Art of Stat is a with in-app purchases Android app in the Education category, developed by Bernhard Klingenberg, Art of Stat. First released 1 month ago(Jan 2026), the app has accumulated 64+ total installs
Recent activity: 21 installs this week (64 over 4 weeks) View trends →
Store info: Last updated on Google Play on Jan 28, 2026 .
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App Description
Your gateway to understanding Statistics and Data Science — better than AI.
The Art of Stat app covers all your statistics and data science needs: from core concepts and probability distributions to data exploration, inference, modeling, and prediction.
Free 7‑day trial, no credit card required.
Use pre‑implemented datasets, import your own CSV/Excel files or, for smaller datasets, provide them directly.
Created by an expert college professor with many years of experience teaching Statistics & Data Science.
Better than AI: a guided, step‑by‑step learning experience—from summary statistics and visualization to understanding statistical methods and outputs, including stunning visualizations. (YouTube channel coming soon!)
Learn Statistics & Data Science the right way. Unmatched visuals and interactivity. Not a photo HW solver.
The app includes seven modules:
- EXPLORE DATA
Summary statistics, contingency tables, correlations, and rich visualizations: bar/pie charts, histograms, boxplots (including side‑by‑side), dotplots, and interactive scatterplots with color‑by‑variable.
- DISTRIBUTIONS
Interactively explore probabilities and percentiles for key distributions (Normal, Student‑t, Binomial, and more). Includes simulation tools.
- CONCEPTS
Central Limit Theorem (means/proportions), correlation and regression, confidence‑interval coverage, and Type I/II errors with power visualization.
- INFERENCE
Confidence intervals and hypothesis tests for proportions and means (one/two samples, independent/dependent), Chi‑square tests, and ANOVA.
- REGRESSION
Simple, multiple, and logistic regression; inference for parameters (SEs, CIs, p‑values); predictions; and striking interaction visualizations.
- MACHINE LEARNING
Supervised and unsupervised methods with train/test split, visualizations, predictions, heatmaps, and accuracy metrics including confusion matrices.
- RESAMPLING
Bootstrap CIs and permutation tests for means, medians, proportions, correlation, slope, and Chi‑square independence.
Includes a Data Editor if you want to to create your own, smaller datasets.
Works offline — perfect for exams or low‑connectivity environments.