Open AccessDescribing data well in r-instat
Author(s) -
Maxwell Fundi,
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Lily Clements,
Daniel Stern,
R. D. Stern,
François Renaud,
Alex Sananka,
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Publication year - 2017
Language(s) - English
Resource type - Conference proceedings
DOI - 10.52041/srap.17203
Subject(s) - meaning (existential) , descriptive statistics , statistical software , open source software , computer science , software , statistical analysis , psychology , mathematics education , knowledge management , data science , statistics , mathematics , psychotherapist , programming language
In 21st century, there is an increasing need to have skills to derive meaning from the growing data around us. In Africa, too much of statistical teaching is theoretical. This leaves students with a lack of data handling skills, and often unprepared to find meaning in data. The African Data Initiative (ADI) aims to change this. A first step has been to develop R-Instat, an open-source, free software based on the increasingly used statistics software R. This paper explains some of the decisions behind R-Instat’s approach to encouraging descriptive analysis. It also proposes how this could support the teaching of good descriptive statistics.