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If you want to publish worthwhile results, or defend your conclusions, or critically evaluate others' work, this is invaluable.
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Our pages are not designed for tiny screens, very slow connections, or text-only displays.
- If you are unsure try a peep inside.
R is a free software environment for statistical computing and graphics. For more information see the introduction to R, or the Wikipedia page.
- R requires Windows, Mac, or Linux.
- You can download the latest 'binary file for a base distribution' free.
- Base-R for Windows and base-R for MAC include a graphical user interface.
- R for Linux does not, but you can run Windows R on a virtual Windows system using VirtualBox (which is also free).
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![]() Biology, images, analysis, design... |
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"It has long been an axiom of mine that the little things are infinitely the most important" |
Peep inside
image copyright Shutterstock/ YAKOBCHUK VASYL, 18percentgrey |
Authors: | Bob Brightwell and Bob Dransfield |
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Publisher: | InfluentialPoints (2013) | |||
Format: | Online access from a secure folder. 1200 hypertext pages (= 4000 A4 pages). 6000 illustrations. 100's of worked examples. 1000's of notes & refs, + R-code. How to get R (it is free). |
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Availability: | How to get access. | |||
Description: | 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. |
| Our hypertext pages can be displayed by most devices with a reasonably up-to-date browser.
- Out-of-date browsers display this arrow → as a rectangle: ▭, or like this: → Our pages are not designed for tiny screens, very slow connections, or text-only displays. - If you are unsure try a peep inside. | ![]() ![]() ![]() ![]() | |||||
| R is not essential for reading this book, only for doing the excercises (they include an intro for those new to R).
R is a free software environment for statistical computing and graphics. For more information see the introduction to R, or the Wikipedia page. | ![]() | |||||
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