jamovi
JASP
Statista
Montecarlito
IBM ILOG CPLEX Optimization Studio
BlueSky Statistics
datarobot
Displayr
GitBook
Mintlify
Docusaurus
ReadMe
Archbee.io
Confluence
Git
Atlassian Bitbucket Server
jamovi has one of the most attractive user interfaces. Even the colors used for window-dressing match the default colors for its graphs. Like JASP, its dialogs provide instant results as each item is checked off. That immediate feedback feels great! Corrections to data values are also immediately reflected in each piece of output that would be affected. However, this also means that you can't do one step, restructure the data, then do another since jamovi requires each step to have the same data structure. SPSS, Minitab, BlueSky Statistics, and JMP can all do such common data-wrangling tasks. So, if you restructure your data a lot, you'll need to do that with another tool and read the data in separately for each structure. jamovi's menus start out very sparse and you extend them by downloading needed parts later. This is the opposite of similar tools like SPSS, Minitab, and BlueSky Statistics, which show all their capabilities upon installation. That makes it good for beginners who avoid the others' complex menus. Regarding analytic methods, jamovi has the most popular statistics. The main topics it lacks are quality control and machine learning/AI. Also, it cannot save models for making predictions on a different dataset.
Based on our record, GitBook seems to be more popular. It has been mentiond 6 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
GitBook is simple and clean, and sometimes that’s exactly what you need. I like it for early-stage products or teams with lighter documentation. You’ll eventually hit limits if your structure gets more complex, but if simplicity is your priority, it’s a solid choice. - Source: dev.to / 10 months ago
TL,DR: LaunchDarkly is great for B2C companies. Bucket is for B2B SaaS products, like GitBook — a modern, AI-integrated documentation platform. - Source: dev.to / over 1 year ago
Addison Schultz, Developer Relations Lead at GitBook, puts it simply:. - Source: dev.to / over 1 year ago
Good question that led to insightful responses. I would like to bring GitBook (https://gitbook.com) too to the comparison notes (no affiliation). They, too, focus on the collaborative, 'similar-to-git-workflow', and versioned approach towards documentation. Happy to see variety in the 'docs' tools area, and really appreciate it being FOSS. Looking forward to trying out Kalmia on some project soon. - Source: Hacker News / about 2 years ago
You can have both a landing page (e.g.: www.your-project.dev) and a documentation website (e.g.: docs.your-project.dev). For creating documentation website GitBook is better fit than Gitlanding. GitBook is free for open source Projects (you just need to issue a request). - Source: dev.to / over 4 years ago
JASP - JASP, a low fat alternative to SPSS, a delicious alternative to R.
Mintlify - The AI-powered documentation writer. It's documentation that just appears as you build
Statista - The Statistics Portal for Market Data, Market Research and Market Studies
Docusaurus - Easy to maintain open source documentation websites
Montecarlito - MonteCarlito is a free Excel-add-in to do Monte-Carlo-simulations.
ReadMe - A collaborative developer hub for your API or code.