Overview
- Unique approach that includes novel topics for introductory courses, including: bootstrapping, Walsh averages, and jackknifing
- Engaging examples and exercises draw readers in and facilitate work by hand and with calculators and statistical software
- Designed for use inside and outside statistics departments
- Accompanying data sets and R code make this textbook easy to use for students and instructors
- Includes supplementary material: sn.pub/extras
Part of the book series: Springer Texts in Statistics (STS)
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About this book
This textbook is designed to give an engaging introduction to statistics and the art of data analysis. The unique scope includes, but also goes beyond, classical methodology associated with the normal distribution. What if the normal model is not valid for a particular data set? This cutting-edge approach provides the alternatives. It is an introduction to the world and possibilities of statistics that uses exercises, computer analyses, and simulations throughout the core lessons. These elementary statistical methods are intuitive. Counting and ranking features prominently in the text. Nonparametric methods, for instance, are often based on counts and ranks and are very easy to integrate into an introductory course.​ The ease of computation with advanced calculators and statistical software, both of which factor into this text, allows important techniques to be introduced earlier in the study of statistics. This book's novel scope also includes measuring symmetry with Walsh averages, finding a nonparametric regression line, jackknifing, and bootstrapping​. Concepts and techniques are explored through practical problems. Quantitative reasoning is at the core of so many professions and academic disciplines, and this book opens the door to the most modern possibilities.
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Keywords
Table of contents (12 chapters)
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Front Matter
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Back Matter
Authors and Affiliations
About the authors
Douglas A. Wolfe is a Professor Emeritus in the Department of Statistics at The Ohio State University. Much of his current research is in ranked set sampling. He is also the author of a popular textbook on nonparametric statistics. Grant Schneider is a Data Scientist at Upstart Network in the San Francisco Bay area. Grant created the accompanying R package and is experienced with statistical programming for research and in the classroom. He received his PhD in Statistics from The Ohio State University.
Bibliographic Information
Book Title: Intuitive Introductory Statistics
Authors: Douglas A. Wolfe, Grant Schneider
Series Title: Springer Texts in Statistics
DOI: https://doi.org/10.1007/978-3-319-56072-4
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer International Publishing AG 2017
Softcover ISBN: 978-3-319-56070-0Published: 18 October 2017
eBook ISBN: 978-3-319-56072-4Published: 09 October 2017
Series ISSN: 1431-875X
Series E-ISSN: 2197-4136
Edition Number: 1
Number of Pages: XVIII, 976
Number of Illustrations: 34 b/w illustrations, 86 illustrations in colour
Topics: Statistical Theory and Methods, Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences, Statistics for Social Sciences, Humanities, Law