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Seeing Theory

Seeing Theory
Seeing Theory is a project designed and created by Daniel Kunin with support from Brown University's Royce Fellowship Program. 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.

http://students.brown.edu/seeing-theory/

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A036057 M. F. Hasler, Table of n, a(n) for n = 1..844 (data from E. Learn to Play Chess Chess Corner Home Learn Play Games Fun World Champions Ecards Book Store Links Learn to Play Chess Unlearning descriptive statistics If you've ever used an arithmetic mean, a Pearson correlation or a standard deviation to describe a dataset, I'm writing this for you. Better numbers exist to summarize location, association and spread: numbers that are easier to interpret and that don't act up with wonky data and outliers. Statistics professors tend to gloss over basic descriptive statistics because they want to spend as much time as possible on margins of error and t-tests and regression. Fair enough, but the result is that it's easier to find a machine learning expert than someone who can talk about numbers. Forget what you think you know about descriptives and let me give you a whirlwind tour of the real stuff.

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