欢迎光临中图云书房,
登录注册

【预售 按需印刷】Statistical Thinking through Media Examples

ISBN9781516565535
作者Anthony Donoghue
出版社Cognella Inc.
按需印刷
装帧名称平装
语言名称英文
页数280
重量690
出版日期2019-06-11
版次1
售价¥915
按需印刷商品,付款后10天内发货
服务按需印刷商品,非质量问题不接受退换货
装帧名称平装
数量
推荐相关系列好书
商品详情

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.