JASP vs R
Side-by-side comparison for macOS
JASP
7.0Statistical analysis application
R
8.0Environment for statistical computing and graphics
| Metric | JASP | R |
|---|---|---|
| Category | Science | Developer Tools |
| AI Score | 7.0 | 8.0 |
| 30-day Installs | 32 | 1.1K |
| 90-day Installs | 79 | 3.0K |
| 365-day Installs | 335 | 11.7K |
| Version | 0.96.0.0 | 4.6.0,sonoma |
| Auto-updates | No | No |
| Deprecated | No | No |
| GitHub Stars | 936 | — |
| GitHub Forks | 230 | — |
| Open Issues | 20 | — |
| License | AGPL-3.0 | — |
| Language | C++ | — |
| Last GitHub Commit | 1mo ago | — |
| First Seen | Jul 18, 2016 | Mar 2, 2019 |
Reviews
JASP
JASP is a statistical analysis application that offers both Bayesian and Frequentist methods, making it a versatile tool for researchers and statisticians. It is designed to be user-friendly, particularly for those familiar with SPSS.
JASP performs statistical analysis using both Bayesian and Frequentist methods.
Pros
- + Supports both Bayesian and Frequentist statistical methods
- + User-friendly interface for SPSS users
- + Actively maintained with recent updates
Cons
- - No auto-update feature
- - Limited community discussion and engagement
R
R is a powerful environment for statistical computing and graphics, widely used in academia and data science. It offers extensive packages and tools for data analysis, visualization, and machine learning, making it indispensable for researchers and statisticians.
R provides an environment for statistical analysis, data visualization, and programming.
Pros
- + Extensive statistical and graphical capabilities
- + Large ecosystem of packages and tools
- + Active and supportive community
Cons
- - Steep learning curve for beginners
- - Some enterprise features require additional tools