Head-to-head · Statistics Learning Software
Conceptual Learning with Interactive Applets vs Seeing Theory
Conceptual Learning with Interactive Applets leads on 1 check, Seeing Theory on 0, and 4 are even. Who comes out ahead on the 5 yes/no, price and count checks where we have data for both products. The editor score weighs everything else too.
Our verdict
- Highest scoreConceptual Learning with Interactive Applets · 9.1/10
- Free planboth
- Most featuresConceptual Learning with Interactive Applets · 4 of 4
Conceptual Learning with Interactive Applets scores higher on our rubric for statistics learning software: 9.1 against 8.8 out of 10; our editors rank them #3 and #6.
Conceptual Learning with Interactive Applets offers classroom tools; Seeing Theory doesn't publish it.
Conceptual Learning with Interactive Applets is the better fit for visualizing statistics concepts in class. Seeing Theory is the better fit for learning probability and inference through visualizations.
- Conceptual Learning with Interactive Applets fits best
Visualizing statistics concepts in class
- Seeing Theory fits best
Learning probability and inference through visualizations
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Side by side
| Feature | Conceptual Learning with Interactive Applets 9.1/10 Visit ↗ | Seeing Theory 8.8/10 Visit ↗ |
|---|---|---|
| At a glance | ||
| Editor score | 9.1 | 8.8 |
| Ranking | #3 in Statistics Learning Software | #6 in Statistics Learning Software |
| Best for | Visualizing statistics concepts in class | Learning probability and inference through visualizations |
| Pricing model | Free | Free |
| Starting price | Not published | Not published |
| Free plan | ✓ | ✓ |
| Free trial | — | — |
| Deployment | Cloud | Cloud |
| Platforms | Web | Web |
| Built for | Solo, Small business, Mid-market | Solo, Small business |
| Features Conceptual Learning with Interactive Applets 4/4 · Seeing Theory 3/4 | ||
| Guided lessons | ✓ | ✓ |
| Statistics simulations | ✓ | ✓ |
| Probability experiments | ✓ | ✓ |
| Classroom tools | ✓ (best) | Not published |
| Specs | ||
| Supported platforms | web | Web browser |
| Our review | ||
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| Our verdict | Conceptual Learning with Interactive Applets is a University of Melbourne educational resource for teaching and learning undergraduate mathematics and statistics. Its browser-based GeoGebra applets are suited to instructors demonstrating… Read the review → |
Seeing Theory is a browser-based educational resource from Brown University that introduces probability and statistics through interactive visualizations. Its six chapters address basic and compound probability, distributions, frequentist… Read the review → |
Strengths and trade-offs
Conceptual Learning with Interactive Applets — where it wins
- Interactive applets cover probability, sampling, inference, regression and ANOVA.
- Visualizations explore confidence intervals, p-values and statistical power.
- Instructor notes and tutorial activities support teaching and student review.
Where it doesn't
- The collection focuses on learning concepts rather than broader classroom management.
- Applets run on the web, with no other supported platform listed.
- Its listed support channels are email and documentation.
Seeing Theory — where it wins
- Interactive demonstrations cover probability events and distributions.
- Visual exercises explain confidence intervals, bootstrap, and Bayesian updating.
- Regression, correlation, and ANOVA examples use interactive visualizations.
Where it doesn't
- The site is archived for reference rather than presented as an active course.
- It runs in a web browser, with no other platform specified.
- Its examples focus on statistical concepts rather than classroom workflows.
- Conceptual Learning with Interactive Applets9.1/10 · Free plan
A free, browser-based collection for visualizing core statistics concepts in class.
Visit the appletsFull verdict → - Seeing Theory8.8/10 · Free plan
A free browser-based resource for exploring probability, inference, and regression visually.
Visit Seeing TheoryFull verdict →
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Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026
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