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 Title Seeing Theory: A Visual Introduction to Probability and Statistics
 Author(s) Daniel Kunin, Jingru Guo, Tyler Dae Devlin, Daniel Xiang
 Publisher: Brown University
 Paperback N/A
 eBook PDF
 Language: English
 ISBN10/ASIN: N/A
 ISBN13: N/A
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Book Description
Seeing Theory was created by Daniel Kunin while an undergraduate at Brown University. The goal of this website is to make statistics more accessible through interactive visualizations (designed using Mike Bostock’s JavaScript library D3.js).
Statistics is quickly becoming the most important and multidisciplinary field of mathematics. According to the American Statistical Association, statistician is one of the top ten fastestgrowing occupations and statistics is one of the fastestgrowing bachelor degrees. Statistical literacy is essential to our data driven society.
Despite 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.
The authors believe that it is far more important for a student to develop statistical intuition than to be able to recite equations. They have developed a collection of 15 interactive visualizations, each of which presents a bitesized concept that is encountered in an introductory statistics curriculum. By using visual explanations, we're able to reach students for whom purely mathematical notation is all but impenetrable. By using interactive visualizations, we encourage students to engage and explore.
About the Authors N/A
 Statistics, Mathematical Statistics, and SAS Programming
 Data Processing, Data Analysis and Data Mining
 Probability and Stochastic
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