Intuitive Biostatistics: A Nonmathematical Guide to Statistical Thinking
Thoroughly revised and updated, the second edition of Intuitive Biostatistics retains and refines the core perspectives of the previous edition: a focus on how to interpret statistical results rather than on how to analyze data, minimal use of equations, and a detailed review of assumptions and common mistakes. Intuitive Biostatistics, Completely Revised Second Edition, provides a clear introduction to statistics for undergraduate and graduate students and also serves as a statistics refresher for working scientists.
NEW TO THIS EDITION:
* Chapter 1 shows how our intuitions lead us to misinterpret data, thus explaining the need for statistical rigor.
* Chapter 11 explains the lognormal distribution, an essential topic omitted from many other statistics books.
* Chapter 21 contrasts testing for equivalence with testing for differences.
* Chapters 22, 23, and 40 explore the pervasive problem of multiple comparisons.
* Chapters 24 and 25 review testing for normality and outliers.
* Chapter 35 shows how statistical hypothesis testing can be understood as comparing the fits of alternative models.
* Chapters 37 and 38 provide a brief introduction to multiple, logistic, and proportional hazards regression.
* Chapter 46 reviews one example in great depth, reviewing numerous statistical concepts and identifying common mistakes.
* Chapter 47 includes 49 multi-part problems, with answers fully discussed in Chapter 48.
* New Q and A sections throughout the book review key concepts.
What people are saying - Write a review
Review: Intuitive Biostatistics: A Nonmathematical Guide to Statistical ThinkingUser Review - Nancy - Goodreads
Excellent self-help book for laboratory scientists in understanding concepts of basic biostatistics. Written by the creator of GraphPad Prism, a common quick statistics software used by lab scientists ... Read full review
Review: Intuitive Biostatistics, First EditionUser Review - Alexander Shearer - Goodreads
An excellent introduction to a wide breadth of statistics with a focus on (1) practical application and (2) the true theoretical basis and not (3) a bunch of math problems. Read full review