Download or read book Statistical Thinking Through Media Examples written by Anthony Donoghue and published by . This book was released on 2018-12-31 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 master's 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.