Practical Statistics for Environmental and Biological Scientists

John Townend is the author of Practical Statistics for Environmental and Biological Scientists, published by Wiley.

"The reassuring tone and straightforward approach of the book would be a useful guide...” (Biochemistry and Molecular Education, July/August 2002) "...covers the basics of designing an experiment/survey, data analysis and presentation, and specific methods." (SciTech Book News, Vol. 26, No. 2, June 2002)"...a good and clear exposition of basic statistical techniques..." (Biometrics, December 2002)"…This no-nonsense approach to elementary statistics should get you or your student started…" (European Journal of Soil Science, March 2003)"...This book provides a concise,   userfriendly, non-technical introduction to statistics". (Metrohm Information, Vol.32, No.1, 2003)

• Preface ixPart I Statistics Basics 11 Introduction 31.1 Do you need statistics? 31.2 What is statistics? 41.3 Some important lessons I have learnt 51.4 Statistics is getting easier 61.5 Integrity in statistics 71.6 About this book 82 A Brief Tutorial on Statistics 92.1 Introduction 92.2 Variability 92.3 Samples and populations 102.4 Summary statistics 112.5 The basis of statistical tests 192.6 Limitations of statistical tests 243 Before You Start 273.1 Introduction 273.2 What statistical methods are available? 283.3 Surveys and experiments 333.4 Designing experiments and surveys — preliminaries 353.5 Summary 434 Designing an Experiment or Survey 454.1 Introduction 454.2 Sample size 454.3 Sampling 504.4 Experimental design 564.5 Further reading 605 Exploratory Data Analysis and Data Presentation 635.1 Introduction 635.2 Column graphs 655.3 Line graphs 675.4 Scatter graphs 695.5 General points about graphs 715.6 Tables 735.7 Standard errors and error bars 746 Common Assumptions or Requirements of Data for Statistical Tests 776.1 Introduction 776.2 Common assumptions 816.3 Transforming data 84Part II Statistical Methods 917 t-tests and F-tests 937.1 Introduction 937.2 Limitations and assumptions 947.3 t-tests 957.4 F-test 1037.5 Further reading 1058 Analysis of Variance 1078.1 Introduction 1078.2 Limitations and assumptions 1098.3 One-way ANOVA 1118.4 Multiway ANOVA 1198.5 Further reading 1279 Correlation and Regression 1299.1 Introduction 1299.2 Limitations and assumptions 1309.3 Pearson’s product moment correlation 1319.4 Simple linear regression 1359.5 Correlation or regression? 1429.6 Multiple linear regression 1439.7 Comparing two lines 1469.8 Fitting curves 1489.9 Further reading 15110 Multivariate ANOVA 15310.1 Introduction 15310.2 Limitations and assumptions 15410.3 Null hypothesis 15610.4 Description of the test 15610.5 Interpreting the results 15810.6 Further reading 16111 Repeated Measures 16311.1 Introduction 16311.2 Methods for analysing repeated measures data 16611.3 Designing repeated measures experiments 17011.4 Further reading 17012 Chi-square Tests 17312.1 Introduction 17312.2 Limitations and assumptions 17412.3 Goodness of fit test 17512.4 Test for association between two factors 17812.5 Comparing proportions 18112.6 Further reading 18413 Non-parametric Tests 18513.1 Introduction 18513.2 Limitations and assumptions 18813.3 Mann—Whitney U-test 18913.4 Two-sample Kolmogorov—Smirnov test 19113.5 Two-sample sign test 19313.6 Kruskal—Wallis test 19513.7 Friedman’s test 19813.8 Spearman’s rank correlation 20013.9 Further reading 20314 Principal Component Analysis 20514.1 Introduction 20514.2 Limitations and assumptions 20714.3 Description of the method 20714.4 Interpreting the results 20914.5 Further reading 21815 Cluster Analysis 22115.1 Introduction 22115.2 Limitations and assumptions 22215.3 Clustering observations 22315.4 Clustering variables 22615.5 Further reading 228Appendices 229A Calculations for statistical tests 231B Concentration data for Chapters 14 and 15 247C Using computer packages 249D Choosing a test: decision table 261E List of worked examples 265Bibliography 271Index 273