Statistical and data handling skills in biology
 Responsibility
 Roland Ennos, Magnus Johnson.
 Edition
 Fourth edition.
 Publication
 Harlow : Pearson Education, 2018.
 Copyright notice
 ©2018
 Physical description
 xix, 258 pages : illustrations, charts ; 25 cm
At the library
Science Library (Li and Ma)
Stacks
Call number  Status 

QH323.5 .E57 2018  Unknown 
More options
Description
Creators/Contributors
 Author/Creator
 Ennos, A. R., author.
 Contributor
 Johnson, Magnus, author.
Contents/Summary
 Bibliography
 Includes bibliographical references and index.
 Contents

 Preface Publisher's acknowledgements 1 An introduction to statistics 1.1 Becoming a biologist 1.2 Awkward questions 1.3 Why biologists have to repeat everything 1.4 Why biologists have to bother with statistics 1.5 Why statistical logic is so strange 1.6 Why there are so many statistical tests 1.7 Using the decision chart 1.8 Using this text 2 Dealing with variability 2.1 Introduction 2.2 Examining the distribution of data 2.3 The normal distribution 2.4 Describing the normal distribution 2.5 The variability of samples 2.6 Confidence limits 2.7 Presenting descriptive statistics and confidence limits 2.8 Introducing computer programs 2.9 Calculating descriptive statistics 2.10 Selfassessment problems 3 Testing for normality and transforming data 3.1 The importance of normality testing 3.2 The ShapiroWilk test 3.3 What to do if your data has a significantly different distribution from the normal 3.4 Examining data in practice 3.5 Transforming data 3.6 The complete testing procedure 3.7 Selfassessment problems 4 Testing for differences from an expected value or between two groups 4.1 Introduction 4.2 Why we need statistical tests for differences 4.3 How we test for differences 4.4 One and twotailed tests 4.5 The types of t test and their nonparametric equivalents 4.6 The onesample t test 4.7 The paired t test 4.8 The twosample t test 4.9 Introduction to nonparametric tests for differences 4.10 The onesample sign test 4.11 The Wilcoxon matched pairs test 4.12 The MannWhitney U test 4.13 Selfassessment problems 5 Testing for differences between more than two groups: ANOVA and its nonparametric equivalents 5.1 Introduction 5.2 Oneway ANOVA 5.3 Deciding which groups are different  post hoc tests 5.4 Presenting the results of oneway ANOVAs 5.5 Repeated measures ANOVA 5.6 The KruskalWallis test 5.7 The Friedman test 5.8 Twoway ANOVA 5.9 The ScheirerRayHare Test 5.10 Nested ANOVA 5.11 Selfassessment problems 6 Investigating relationships 6.1 Introduction 6.2 Examining data for relationships 6.3 Examining graphs 6.4 Linear relationships 6.5 Statistical tests for linear relationships 6.6 Correlation 6.7 Regression 6.8 Studying common nonlinear relationships 6.9 Dealing with nonnormally distributed data: rank correlation 6.10 Selfassessment problems 7 Dealing with categorical data 7.1 Introduction 7.2 The problem of variation 7.3 The x2 test for differences 7.4 The x2 test for association 7.5 Validity x2 of tests 7.6 Logistic regression 7.7 Selfassessment problems 8 Designing experiments 8.1 Introduction 8.2 Preparation 8.3 Excluding confounding variables 8.4 Replication and pseudoreplication 8.5 Randomisation and blocking 8.6 Choosing the statistical test 8.7 Choosing the number of replicates: power calculations 8.8 Dealing with your results 8.9 Selfassessment problems 9 More complex statistical analysis 9.1 Introduction to complex statistics 9.2 Experiments investigating several factors 9.3 Experiments in which you cannot control all the variables 9.4 Investigating the relationships between several variables 9.5 Exploring data to investigate groupings 10 Presenting and writing about statistics 10.1 Introduction  less is more! 10.2 The introduction section 10.3 The methods section 10.4 The results section 10.5 The discussion section 10.6 The abstract or summary Glossary Further reading Solutions Statistical tables Table S1: Critical values for the t statistic Table S2: Critical values for the correlation coefficient r Table S3: Critical values for the x2 statistic Table S4: Critical values for the Wilcoxon T distribution Table S5: Critical values for the MannWhitney U distribution Table S6: Critical values for the Friedman x2 distribution Table S7: Critical values for the Spearman rank correlation coefficient r.
 (source: Nielsen Book Data)9781292086033 20180611
 Publisher's Summary
 Is there a link between people's heart rate and blood pressure? Does the lead in petrol fumes affect the growth of roadside plants? The ability to expertly analyse statistical data is a crucial skill in the biological sciences  it is fundamental to fully understanding what your experiments are actually telling you and so being able to answer your research questions. Statistical and Data Handling Skills in Biology gives you everything you need to understand and use statistical tests within your studies and future independent research. Written in a straightforward and easy to understand style it presents all of the tests you will need throughout your studies, and shows you how to select the right tests to get the most out of your experiments. All of this is done in the context of biological examples so you can see just how relevant a skill this is, and how becoming fully proficient will make you a more rounded scientist. This 4th edition has been thoroughly updated throughout and now includes detailed coverage of the free statistical package R studio and a new chapter on how to write about and present statistics in papers, theses and reports. The first chapter has also been revised to introduce students to the need for and ideas behind statistical analysis. Features * Clear explanation with step by step detail of how to carry out a wide range of statistical analyses will help you to quickly gain understanding and confidence in this essential area. * Useful decision charts will help you to select the right statistical test and gain confidence in answering your research questions. * Real world examples in each chapter will help you to develop an applied understanding of the full range of statistical techniques * Selfassessment problems scenarios at the end of each chapter enable you to practice applying your understanding of a technique, thereby improving your confidence in using numbers. Guided answers allow you to check your understanding. Statistical and Data Handling Skills in Biology 4th edition is ideal for any biomedic or environmental scientist getting to grips with statistical analysis for use in class on as part of independent study.
(source: Nielsen Book Data)9781292086033 20180611
Subjects
 Subject
 Biometry.
Bibliographic information
 Publication date
 2018
 Copyright date
 2018
 Note
 Originally published: 2000.
 Previous edition: 2012.
 ISBN
 1292086033 paperback
 9781292086033 paperback
 1292086068 electronic book PDF
 9781292086064 electronic book PDF
 1292133112 electronic book ePub
 9781292133119 electronic book ePub