New R package xplain: Providing interactive interpretations and explanations of statistical results

June 3, 2018
By

(This article was first published on Topics in R, and kindly contributed to R-bloggers)

The package xplain is designed to help users interpret the results of their statistical analyses.

It does so not in an abstract way as textbooks do. Textbooks do not help the user of a statistical method understand his findings directly. What does a result of 3.14 actually mean? This is often hard to answer with a textbook alone because the book may provide its own examples but cannot refer to the specifics of the user’s case. However, as we all know, we understand things best when they are explained to us with reference to the actual problem we are working on. xplain is made to fill this gap that textbooks (and other learning materials) leave.

The basic idea behind xplain is simple: Package authors or other people intested in explaining statistics provide interpretation information for a statistical method (i.e. an R function) in the format of an XML file. With a simple syntax this interpretation information can reference the results of the user’s call of the explained R function. At runtime, xplain then provides the user with textual interpretation that really relates to his/her case.

Providing xplain interpretation information can be interesting for:

  • R package authors who implement a statistical method
  • statisticians who develop statistical methods themselves
  • college and university teachers who want to make their teaching content more accessible for their students
  • everybody who enjoys teaching and explaining statistics and thinks he/she has something to contribute

xplain offers support for interpretation information in different languages and on different levels of difficulty.

Read the xplain web tutorial to learn everything about how to use xplain: http://www.zuckarelli.de/xplain/index.html.

More ressources on xplain:

To leave a comment for the author, please follow the link and comment on their blog: Topics in R.

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