Biology, images, analysis, design...
|"It has long been an axiom of mine that the little things are infinitely the most important" |
image copyright Shutterstock/ YAKOBCHUK VASYL, 18percentgrey
|Avoiding and Detecting Statistical Malpractice:
Design and analysis for biologists, with R
|Authors:||Bob Brightwell and Bob Dransfield|
|Price:||£ 24.99 (free to try)|
|Delivery:||Free and immediate: Download 55MB setup-file for Windows.|
|Format:||Hyperbook (advanced-format hypertext ebook including Windows viewer).
1200 hypertext pages (= 4000 A4 pages). 6000 illustrations. 100's of worked examples. 1000's of notes & refs, + R-code.
This is a practical, up-to-date, interactive biostatistics course and reference work for undergraduate or postgraduate biologists.
- It shows how readily malpractice can be identified in statistical analyses, and critically evaluates a huge variety of medical, veterinary, and ecological examples.
- It evaluates the reasons for statistical malpractice, from ignorance to mistakes to fraud.
- It clarifies the conflicting terminology, explains the statistical controversies, and reviews common errors in design, analysis and interpretation.
- It describes the popular study designs, plus many advanced ones - and examines their reasoning, strengths and weaknesses.
- It explores the reasoning behind statistical analyses (including worked examples) and explains how they are affected by their assumptions, study design, and data.
- It uses simulation models to explore the logic and assumptions that underlie the standard formulae, and exposes their behaviour when those assumptions hold - or when they fail.
If you want to publish worthwhile results, or defend your conclusions, or critically evaluate others' work, this is invaluable.
|home sitemap about us|