Biomeasurement
A Student's Guide to Biological Statistics
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Product details:
- Edition number 4
- Publisher OUP Oxford
- Date of Publication 2 May 2019
- ISBN 9780198807483
- Binding Paperback
- No. of pages384 pages
- Size 245x190x19 mm
- Weight 650 g
- Language English 0
Categories
Short description:
A refreshing, student-focused introduction to the use of statistics in the study of the biosciences. Emphasising why statistical techniques are essential tools for bioscientists, Biomeasurement removes the stigma attached to statistics by giving students the confidence to use key techniques for themselves.
MoreLong description:
Statistical analysis allows us to attach meaning to data that we have collected; it helps us to understand what experimental results really mean, and to assess whether we can trust what experiments seem to be telling us. Yet, despite being a collection of the most valuable and important tools available to bioscientists, statistics is often the aspect of study most feared by students.
Biomeasurement offers a refreshing, student-focused introduction to the use of statistics in the study of the biosciences. With an emphasis on why statistical techniques are essential tools for bioscientists, the book develops students' confidence to use and further explore the key techniques for themselves.
Beginning by placing the role of data analysis in the context of the wider scientific method and introducing the student to the key terms and concepts common to all statistical tools, the book then guides the student through descriptive statistics, and on to inferential statistics, explaining how and why each type of technique is used, and what each can tell us in order to better understand our data. It goes on to present the key statistical tests, walking the student step-wise through the use of each, with carefully-integrated examples and plentiful opportunities for hands-on practice. The book closes with an overview of choosing the right test to suit your data, and tools for presenting data and their statistical analyses.
Written by a talented educator, whose teaching has won praise from the UK's Quality Assurance Agency for Higher Education, Biomeasurement is sure to engage even the most wary of students, demonstrating the power and importance of statistics throughout the study of bioscience.
Online resources:
The online resources to accompany Biomeasurement include:
For students:
· Screencast walkthroughs for SPSS and R.
· Online glossary and flashcard glossary.
· Data sets, for use in statistical analysis software packages.
· Help sheets offering concise guidance on key techniques and the use of statistical analysis software packages.
· Interactive calculation sheets to help students carry out key statistical tests quickly and easily in Excel, without the need for other software.
· Full-text versions of Literature Link articles from OUP Journals.
For registered adopters of the book:
· Additional exercises, to supplement those in the book, and suggested tutorial assignments.
· Figures from the book, available for download.
· PowerPoint presentation outlines for each chapter.
Review from previous edition Biomeasurement does a wonderful job of keeping the biology the focus of analysis, and highlighting the fact that statistics is simply another useful tool to help biological understanding.
Table of Contents:
Why am I reading this book?
Getting to grips with the basics
Describing a single sample
Inferring and estimating
Choosing the right test and graph
Overview of null hypothesis significance testing
Tests on frequencies
Tests of difference: two unrelated samples
Tests of difference: two related samples
Tests of difference: more than two samples
Tests of relationship: regression
Tests of relationship: correlation
Introducing the generalized linear model: general linear model
More on the generalized linear model: logistic and loglinear models
Appendix I How to enter data into SPSS
Appendix II Statistical tables of critical values
Appendix III Summary guidance on reporting statistical results
Appendix IV Statistics and experimental design
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