Table of contents
JASP
JASP, a low fat alternative to SPSS, a delicious alternative to R.
As JASP is an open source project, you can find more
open source alternatives and stats
on LibHunt.
User-Friendly Interface
JASP offers an intuitive and visually appealing interface that is easy for users to navigate, making statistical analysis accessible even to those who are not heavily experienced in statistics.
Open Source
Being open-source, JASP is available for free, enabling anyone to use it without financial barriers and allowing for community-driven improvements and customizations.
Bayesian Methods
JASP includes a wide array of Bayesian statistical tools, providing advanced options for users interested in Bayesian inference, which is often not as well-supported in other statistical software.
Integration with R
JASP allows for integration with R, providing flexibility for users who wish to perform more customized or complex analyses by incorporating R scripts within the user-friendly JASP environment.
Dynamic Reports
The software enables users to generate dynamic reports that update in real-time as data changes, streamlining the reporting process and making it easier to share findings.
Promote JASP. You can add any of these badges on your website.
JASP works very similarly to jamovi. That's not a coincidence, as some JASP developers split off to create jamovi. You can open a single dataset and use the most popular statistics and machine learning methods. But if you have multiple datasets to merge, you must do that in another tool. Also, the dataset must maintain a single structure throughout your analyses. Restructuring or transposing is not allowed. It is commonly said that data scientists spend 80% of their time wrangling data like that, so that's a significant limitation for general use. However, those simplifications make JASP a good choice for teaching. Another advantage for teaching is that the menus are very sparse, but you can add to them easily by downloading additional modules. That's the opposite of similar software such as BlueSky Statistics, SPSS, or Minitab, which install all features at once. If you're looking for free and open-source software, JASP and jamovi are best for teaching while BlueSky Statistics is best for general-purpose analysis.
JASP is considered a good tool for statistical analysis, especially for educational purposes and for those who need a cost-effective solution that doesnโt sacrifice functionality.
We have collected here some useful links to help you find out if JASP is good.
Check the traffic stats of JASP on SimilarWeb. The key metrics to look for are: monthly visits, average visit duration, pages per visit, and traffic by country. Moreoever, check the traffic sources. For example "Direct" traffic is a good sign.
Check the "Domain Rating" of JASP on Ahrefs. The domain rating is a measure of the strength of a website's backlink profile on a scale from 0 to 100. It shows the strength of JASP's backlink profile compared to the other websites. In most cases a domain rating of 60+ is considered good and 70+ is considered very good.
Check the "Domain Authority" of JASP on MOZ. A website's domain authority (DA) is a search engine ranking score that predicts how well a website will rank on search engine result pages (SERPs). It is based on a 100-point logarithmic scale, with higher scores corresponding to a greater likelihood of ranking. This is another useful metric to check if a website is good.
The latest comments about JASP on Reddit. This can help you find out how popualr the product is and what people think about it.
For anyone looking for a quick and hands-on dive into the world of Bayesian modelling and inference, I can't recommend JASP enough, made freely available by the University of Amsterdam[0]. I've recommended it before, and it's just a breeze to work with, seeing frequentist and Bayesian analyses side-by-side. [0]: https://jasp-stats.org/. - Source: Hacker News / over 1 year ago
Anyone looking to apply and compare frequentist and bayesian methods within a unified GUI (which is essentially an elegant wrapper to R and selected/custom statistical packages), should check out JASP developed by the University of Amsterdam [0]. It's free to use, and the graphs + captions generated on each step are of publication quality out of the box. Using it truly feels like a 'fresh way' to do... - Source: Hacker News / over 2 years ago
Https://jasp-stats.org fully free. Its advisible to learn python, R or matlab for graduate school. Source: about 3 years ago
Also for alternative software that are much easier to use take a look at JASP or jamovi (both are very similar); and as a bonus, neither of these two will require you to manually add product variables to your dataset. Source: about 3 years ago
If you have no access to SPSS (or SAS, or JMP), then look into JASP (https://jasp-stats.org/). I've only just touched that. One thing I believe is that JASP (as well as JMP) will allow/block off tests and analyses depending on the nature of each column. This means that, for example, if you have groups A, ..., Z, the software will treat those as non-numbers, which can only be used as inputs for variables which... Source: about 3 years ago
If you're looking for a stop-gap Stats software while you learn R, try JASP. It's a free statistical analysis software which runs on R. Https://jasp-stats.org/. Source: over 3 years ago
There may be, there's also JASP, which is similar to SPSS. However, working on product teams, the ability to manipulate large datasets is lost there. I find that skill to be really useful for many things not even quant (like cleaning a dataset from a DS to send out qualitative interview screeners). Source: over 3 years ago
Use JASP, at least take a look at it: https://jasp-stats.org/ it's free and open source, is more user friendly than SPSS, and does a lot of what Mplus does (because it uses R in the background). Source: over 3 years ago
If you're looking for a menu driven statistics software that is free, have a look at JASP or jamovi. Source: almost 5 years ago
The other interesting discovery I made is that there is now a desktop program called JASP which can do a lot of stats out of the box, including both the Bayesian binomial test we've been playing with, and the Chi-square test. This is a positive development from the situation five years ago, when it was necessary for me to learn the R programming to do anything serious with stats or Data Science. Source: about 5 years ago
You might also be interested in JASP and JAMOVI, they are free / open source and really good! Source: about 5 years ago
Or you can try JASP (https://jasp-stats.org/). Source: about 5 years ago
I've been having a lot of fun using JASP in my learning of statistics. The way they integrate with R is quite promising. And even more the way they deliver by default the possibility to choose between a frequentist approach and a Bayesian approach for your analysis. Have you heard of them? JASP stats. Source: about 5 years ago
Also for Stats stuff, maybe checkout JASP, one of the professors I support used it last year as an alternative to SPSS. Source: about 5 years ago
Have you looked into JASP? Pretty sure its build on R code. https://jasp-stats.org/. Source: over 5 years ago
JASP, or Jeffreysโs Amazing Statistics Program, is increasingly recognized within the software industry as a competitive and user-friendly statistical analysis tool. Public opinion, as gathered from various recent mentions and reviews, depicts JASP as a robust and versatile platform designed to meet the needs of both researchers and students.
A significant portion of JASP's appeal stems from its seamless integration of Bayesian analysis, which many users have highlighted as a core feature setting it apart from traditional statistical software like SPSS. The simplicity and accessibility of its user interface resonate well with those seeking a more intuitive experience. The side-by-side presentation of frequentist and Bayesian analyses within its GUI is particularly appreciated, offering a fresh and comprehensive approach to statistical analysis.
JASP's free and open-source model is frequently praised, particularly by those who are deterred by the cost barriers associated with other statistical software. This open-access approach is seen as democratizing the availability of powerful statistical tools, a sentiment often shared in contexts where JASP is compared to commercial alternatives like SPSS or paid software such as JMP.
Functionality-wise, JASP boasts a streamlined data import and export process, and its automated approach to generating publication-quality graphs and captions is emphasized as a key benefit. Users often commend its Office 365-style layout that simplifies navigation and data manipulation. However, some have noted that JASP requires external data preparation, such as handling missing values, which can be a downside for users accustomed to more integrated data preprocessing options.
Compatibility with other software ecosystems is an added advantage. By operating as a sophisticated wrapper around R, JASP allows users to harness the extensive capabilities of R without necessitating proficiency in coding. It effectively lowers the entry barrier for those new to statistical programming while still providing powerful analytical tools.
Feedback from educational contexts suggests that JASP is favored for its clarity and support in learning environments. The platform includes comprehensive tutorials and documentation, which provide substantial pedagogical value. Users have also identified JASP as a viable alternative to other statistical platforms like STATA and Minitab, particularly for Mac users seeking free or lower-cost options.
While JASP is lauded for certain strengths, it is not without its limitations. Concerns are occasionally raised regarding its dependence on R for backend processing, which might not suit workflows requiring more direct dataset manipulation.
In conclusion, JASP stands as a strong contestant in the field of statistical software, offering an advantageous combination of user-friendliness, cost-effectiveness, and powerful analytical capabilities, with particular strength in Bayesian and frequentist statistical methods. Its position as an open-source tool allows for continuous development and improvement, making it a popular choice for many in the data science and educational communities.
Do you know an article comparing JASP to other products?
Suggest a link to a post with product alternatives.
Is JASP good? This is an informative page that will help you find out. Moreover, you can review and discuss JASP here. The primary details have not been verified within the last quarter, and they might be outdated. If you think we are missing something, please use the means on this page to comment or suggest changes. All reviews and comments are highly encouranged and appreciated as they help everyone in the community to make an informed choice. Please always be kind and objective when evaluating a product and sharing your opinion.
Great ๐๐๐๐