专栏名称: 机器学习研究会

机器学习研究会是北京大学大数据与机器学习创新中心旗下的学生组织，旨在构建一个机器学习从事者交流的平台。除了及时分享领域资讯外，协会还会举办各种业界巨头/学术神牛讲座、学术大牛沙龙分享会、real data 创新竞赛等活动。

【推荐】一个非常棒的可视化概率及统计的学习网站

机器学习研究会 · 公众号 · AI · 2017-02-26 21:17

正文

点击上方“机器学习研究会”可以订阅哦

摘要

转自：王威廉

对于学习统计与概率，我发现很多学生的障碍在于无法理解抽象的数学表达。最近常春藤名校布朗大学推出了一个非常棒的可视化概率及统计的学习网站，帮助学生交互式地学习概率及统计学基本概念。

Seeing Theory is a project designed and created by Daniel Kunin with support from Brown University's Royce Fellowship Program and National Science Foundation group STATS4STEM. The goal of the project is to make statistics more accessible to a wider range of students through interactive visualizations.

Statistics, is quickly becoming the most important and multi-disciplinary field of mathematics. According to the American Statistical Association, statistician is one of the top ten fastest-growing occupations and statistics is one of the fastest-growing bachelor degrees. Statistical literacy is essential to our data driven society. Yet, for all the increased importance and demand for statistical competence, the pedagogical approaches in statistics have barely changed. Using Mike Bostock’s data visualization software, D3.js, Seeing Theory visualizes the fundamental concepts covered in an introductory college statistics or Advanced Placement statistics class. Students are encouraged to use Seeing Theory as an additional resource to their textbook, professor and peers.