Describing data well in r-instat

Maxwell Fundi, Lily Clements, D. Stern, R. Stern, François Renaud, Alex Sananka
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引用次数: 1

Abstract

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.
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在r-instat中很好地描述数据
在21世纪,我们越来越需要掌握从我们周围不断增长的数据中获取意义的技能。在非洲,太多的统计学教学是理论性的。这使得学生缺乏数据处理技能,而且往往没有准备好从数据中找到意义。非洲数据倡议(ADI)旨在改变这种状况。第一步是开发R-Instat,这是一个基于越来越多使用的统计软件r的开源免费软件。本文解释了R-Instat鼓励描述性分析方法背后的一些决定。它还提出了如何支持良好的描述性统计教学。
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