This delightful and informative guide from my friends at No Starch Press comes with the following cover blurb: “Statistics Done Wrong is a pithy, essential guide to statistical blunders in modern Science that will show you how to keep your research blunder-free.” It is somewhat pithy, but as to blunder free, I will quote the old maxim that “nothing is foolproof, as fools are so very clever.” Still, the book has much to recommend it.
The author of this wonderful text delivers a brief, easy-to-absorb, yet very comprehensive text...
This is not a text for the novice. However, for those math/statistics aficionados, there is much...
The introduction of newer sequencing methodologies, DNA microarrays and high-throughput...
I can most simply describe this book by quoting from the back cover: Motivation — “…how can you get started in a wide-ranging, interdisciplinary field that’s so clouded in hype?” Background Needed — “If you’re familiar with linear algebra, probability, and statistics, and have programming experience…”
It is always a pleasure to review a text that is easy to read and understand, when targeted to a novice audience. This book was written for business majors at the junior undergraduate level, and not statistics majors. However, it is recommended that readers have a course in introductory statistics before using this book.
It is always a pleasure to review a book on statistics (bias intended)! Especially one that is well-written, compact and well-constructed for its intended audience. Common Errors in Statistics (and How to Avoid Them), 4th Edition, is written for the non-statistician and can be readily assimilated by undergraduate students with a single statistics class under their belt.
Making an intensely complex subject understandable to the non-physicist John A. Wass, Ph.D. Well, relatively! I didn’t ask to review this book, but my wonderful contact at No Starch Press (read Geeks Anonymous) sent The Manga Guide to Relativity thinking that the subject may interest me. After sitting on it for too many months, I finally got around to reading a few pages. After 10 pages, I was hooked
This month’s column reviews a book from three of my former colleagues at Abbott Laboratories. Their areas of expertise are toxicogenomics, pharmacogenomics and oncology. Naturally, the subject matter reflects the authors’ research interests.
As readers of this column probably know, Mathematica is software that does mathematics. Its symbolic code offers not only math, modeling and simulation, but a complete documentation and deployment tool. This cookbook assumes a basic knowledge of the program and is not a beginner’s guide. Rather it ‘jumps right in’ with code and examples. Lots of them!
Many scientists have frequent use for model construction, and as the biological and physical processes are studied and modeled on ever more complex levels, this tool, Model Selection and Model Averaging, would be a very useful addition to the analytic repertoire. Unfortunately the math will be found challenging by many
The fluff, reviewers comment, and marketing hype around this book include such revelations as "Load important statistical concepts directly into your brain" and "Wouldn’t it be dreamy if there was a book on data analysis that wasn’t just a glorified printout of Microsoft Excel help files?" However, this volume is just a little bit different from what you may be used to in an intro book or “Dummies Guide."
The back cover of Modeling Differential Equations in Biology explains that, as college level science students only take the rudiments of calculus, this book fills a gap in teaching the biology students how to use differential equations in their research. The text uses actual scientific papers for examples and, therefore, reinforces the relevance of the methodologies.
All living things are made of cells. And thus begins the adventures of Rin and Ami, two Japanese college students who have skipped too many of their intro molecular biology classes to satisfy the attendance requirement. As a result, their teacher, Professor Moro, has “sentenced” them to a summer of makeup classes on his private island. To facilitate their studies, they use a virtual reality machine
A volume that can be recommended to both statisticians and life scientists The review this month is for Statistical and Computational Pharmacogenomics , an interdisciplinary text by CRC. It turned out to be an exceedingly pleasant experience, as it is a volume that can be recommended to both statisticians and life scientists
After many years of slogging through textbooks that presented too many proofs and demonstrations that were left to the student or lacking numerous intermediate steps, after encountering numerous "introductions" that were obtuse and highly theoretical and after digesting far too many explanations with maximal equations and minimal verbiage, we arrive at the happy medium.
This is something new. Not to the world, but to readers of this column. For those of you not into cartoons or comic books, Manga is (are) a genre of Japanese comic books and cartoons. They are usually drawn in black and white format and cover a wide range of subject matter. Wikipedia has some good background information, in case you are interested.
For those readers who have perused my review of the previous volume on cellular physiology, it is apparent that these interdisciplinary texts are meant to offer a little biology to the engineers and mathematicians and a lot of math to any life scientist bold enough to turn the pages.
The book herein reviewed, the second edition of Mathematical Physiology I: Cellular Physiology, is an interdisciplinary text. The authors state in the preface that their major goals were to expand the discussion of many models and principles from the first edition, and to provide pointers to recent works in as many areas as possible. They have succeeded remarkably well in the first goal
The title here should include “on a Number of Levels,” as this simple text has so much to recommend it. No, it is not watered-down statistics! It is a practical guide to quickly getting the reader up to speed on those items most used in describing data, performing hypothesis testing and conveying some of the more fascinating aspects of statistics in research
What I first encountered was rather sobering, as it was soon apparent that I was in way over my head John A. Wass, Ph.D. The National Institute of Standards and Technology (NIST) recently released five preview chapters of its online Digital Library of Mathematical Functions (DLMF) .
My occasional rants usually involve my twin interests of genomics and the mathematical education of scientists. This month’s column is a natural extension of the latter in that Wolfram’s MathWorld Web site is a nice place for the semi-literate practitioner (or the very astute educator) to get grounding in many areas of mathematics, and perhaps an impetus to upgrade their skills, however slightly.
The second half of the above title comes to us via a delightful feature article in the January 2007 issue of Physics Today . The author, Michael Deem, is a professor of physics and astronomy and biochemical and genetic engineering at Rice University (interesting combo). He begins by stating, "The contemplation and resolution of questions at the interfaces of biology, mathematics and physics promise to lead to a greater understanding ...
ccording to the cover blurb, Mathematics for Physical Chemistry is a text for chemistry undergraduates with emphasis on preparation for physical chemistry courses. As such, it contains the usual exposition, examples and problems, but also may be useful as a review to those in a variety of other fields.
The above title is from a recent report from the National Academies that attempts to identify opportunities and challenges presented by the rapid convergence of knowledge in mathematics and the life sciences. If the interested reader can get by the rather stiff and formal language of the Executive Summary, then the rest of the document is rather good reading
Normally, I would avoid use of the word "programming" in a title for fear of immediately losing my audience but, as my readers seem to be mostly chemists and engineers, I may not have so much to fear (I think). This month's column is a review of a really nice introductory text on programming with the Mathematica language.
The Navigator is one of the more recent additions to the line of books that, by explanation and example, facilitate the use of one of the most popular symbolic/numeric mathematical programs. Mathematica has been reviewed many times in this and other publications and is frequently used software for advanced mathematics