![]() ![]() This cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Other. The cookie is set by GDPR cookie consent to record the user consent for the cookies in the category "Functional". ![]() The cookie is used to store the user consent for the cookies in the category "Analytics". ![]() These cookies ensure basic functionalities and security features of the website, anonymously. Necessary cookies are absolutely essential for the website to function properly. If you want to contribute, take a look at the GitHub repositories which are currently public or contact us if you want to develop a completely new app for the Statsomat. Automizing data analysis interpretation and contributing to Statsomat are fantastic ways to learn Data Science. You are also welcomed to improve and extend the functionality of the apps. Most of the other contributors are students at the University of Applied Sciences Koblenz, Department of Mathematics and Technics. The core contributor responsible for the overall design as well as authoring the content of the apps is Denise Welsch. ![]() Statsomat is a project in continuous progress. If you need a quick help with your data analysis or with programming, then check the Statsomat apps. The reports contain annotated tables, graphics, an interpretation in plain English and the code to reproduce the analysis by yourself. Classic statistical data analysis and Machine Learning questions are handled by the apps in a similar way as by a human. If you are an applied researcher or a Data Science learner unfamiliar with data analysis or programming, you can use the Statsomat apps directly in the browser to generate automated data analysis reports. The strategy we follow is a maximal automation with a minimal, but sufficient user-interaction. The apps are a great help for applied researchers and Data Science learners all over the world. The Statsomat project and site have the goal of developing, collecting and maintaining open-source and web-based apps for automated data analysis with a human-readable interpretation. Coming soon: Bayesian approach for the comparison of two proportions. ![]()
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