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Teaching StatisticsA Bag of Tricks$
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Andrew Gelman and Deborah Nolan

Print publication date: 2017

Print ISBN-13: 9780198785699

Published to Oxford Scholarship Online: September 2017

DOI: 10.1093/oso/9780198785699.001.0001

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Statistical thinking in a data science course

Statistical thinking in a data science course

Chapter:
(p.342) 21 Statistical thinking in a data science course
Source:
Teaching Statistics
Author(s):

Andrew Gelman

Deborah Nolan

Publisher:
Oxford University Press
DOI:10.1093/oso/9780198785699.003.0021

In this chapter, we describe the philosophy, goals, syllabus, and activities for a course that we have developed in data science course. In this course we integrate topics from computing, statistics, and working with data. This integrated approach addresses many core aspects in statistics training, including statistical thinking, the role of context in addressing a statistical problem, statistical communication through code, and the balance between programming and mathematical approaches to problems. When designing this course, we asked ourselves what our students ought to be able to do computationally. While we do provide a list of technical material, we also considered the broader goals of the course. Examples include plotting on Google Earth and developing a spam filter for unwanted email.

Keywords:   Data science, Google Earth, information technologies, programming, spam filter, statistical computing, teaching statistics, text manipulation, visualization

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