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Statistical Thinking through Media Examples

paperbackJune 11, 2019
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ISBN-13: 9781516565535 ISBN-10: 1516565533
Publisher
Cognella Academic Publishing
Binding
paperback
Published
June 11, 2019
Weight
1.2 lbs
Dimensions
25.40×1.50×20.30 cm

About this book

Statistical Thinking through Media Examples by Donoghue, Anthony. paperback edition. ISBN: 9781516565535.

Statistical Thinking through Media Examples uses real-world examples from various media to give students an introduction to fundamentals of statistical thinking. Unlike many standard texts in the discipline, the book focuses on conceptual understanding – the meaning behind mathematical calculations rather than the calculations themselves. Written in accessible language, the book begins by discussing the importance of learning how to assess the quality of research results presented by the media. This understanding creates an essential context for subsequent chapters on questioning study design including polls and surveys, reasoning with variation in data measurements, understanding probability, confidence intervals, hypothesis testing, and linear regression. Students also learn how statistics can be misused and manipulated by researchers to provide a desired result. The second edition features new coverage of select topics, including ANOVA, Chi-Square tests, and multiple linear regression. Every chapter references online resources or includes in-depth discussion to draw connections between statistical concepts and media examples, such as studies on alcohol consumption and cardiovascular health, American football and brain injury, public mass shootings, dishonesty in scientific research, and more. Statistical Thinking through Media Examples is an ideal resource for any course that deals with introductory statistics, particularly those in the health and social sciences, journalism, and business. Anthony Donoghue earned his masters degree in statistics at University College Dublin and has worked as a professional statistician in both Ireland and the United States. Currently, he works as a consultant in New York, providing statistics and programming expertise and training. He is also a statistics faculty member at both Columbia University and New York University, where he teaches statistical computing, statistics, and statistical thinking.