Statistical And Data Handling Skills in Biology

Series
Pearson
Author
Roland Ennos / Magnus Johnson  
Publisher
Pearson
Cover
Softcover
Edition
4
Language
English
Total pages
280
Pub.-date
March 2018
ISBN13
9781292086033
ISBN
1292086033
Related Titles


Product detail

Product Price CHF Available  
9781292086033
Statistical And Data Handling Skills in Biology
45.20 approx. 7-9 days

Free evaluation copy for lecturers


Description

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. 

Statistical and Data Handling Skills in Biology gives you everything you need to master the key skills of statistical analysis. Written in a straight-forward 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.

Features

  • Clear, concise coverage of essential topics to help you to quickly get to grips with statistical concepts and tests.
  • Useful decision charts will help you to select the right statistical test and gain confidence in answering your research questions.
  • Worked examples of real research questions with step by step guidance on how to answer them using a range of statistical techniques will help you to develop an applied and practical understanding.
  • Self-assessment 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.
  • Dedicated chapter covering how to write about and present statistics in papers, theses and reports
  • Step-by-step instructions on how to carry out statistical tests on both a calculator and computer packages.
  • Detailed coverage of how to use R studio and SPSS to carry out analyses to equip you with the flexibility and skills to carry out your own independent research and data analysis.

New to this Edition

  • The first chapter has been thoroughly rewritten to introduce students to the need for and ideas behind statistical analysis to help gain a more considered understanding of the subject. 
  • Coverage of the free statistical package R studio has been incorporated to provide students with the knowledge and skills to develop their own statistical analyses.  
  • New chapter covering how to write about and present statistics in papers, theses and reports will help students to incorporate and convey their statistical results and analysis at a professional level.

Table of 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 Self-assessment problems

3 Testing for normality and transforming data

3.1 The importance of normality testing

3.2 The Shapiro–Wilk 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 Self-assessment 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 two-tailed tests

4.5 The types of t test and their non-parametric equivalents

4.6 The one-sample t test

4.7 The paired t test

4.8 The two-sample t test

4.9 Introduction to non-parametric tests for differences

4.10 The one-sample sign test

4.11 The Wilcoxon matched pairs test

4.12 The Mann–Whitney U test

4.13 Self-assessment problems

5 Testing for differences between more than two groups: ANOVA and its non-parametric equivalents

5.1 Introduction

5.2 One-way ANOVA

5.3 Deciding which groups are different – post hoc tests

5.4 Presenting the results of one-way ANOVAs

5.5 Repeated measures ANOVA

5.6 The Kruskal–Wallis test

5.7 The Friedman test

5.8 Two-way ANOVA

5.9 The Scheirer–Ray–Hare Test

5.10 Nested ANOVA

5.11 Self-assessment 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 non-linear relationships

6.9 Dealing with non-normally distributed data: rank correlation

6.10 Self-assessment 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 Self-assessment 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 Self-assessment 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 Mann–Whitney U distribution

Table S6: Critical values for the Friedman x2 distribution

Table S7: Critical values for the Spearman rank correlation coefficient r

Back Cover

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 straight-forward 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

·    Self-assessment 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.