Practical statistics for environmental and biological scientists / John Townend.

Enhanced descriptions from Syndetics:

All students and researchers in environmental and biological sciences require statistical methods at some stage of their work. Many have a preconception that statistics are difficult and unpleasant and find that the textbooks available are difficult to understand.

Practical Statistics for Environmental and Biological Scientists provides a concise, user-friendly, non-technical introduction to statistics. The book covers planning and designing an experiment, how to analyse and present data, and the limitations and assumptions of each statistical method. The text does not refer to a specific computer package but descriptions of how to carry out the tests and interpret the results are based on the approaches used by most of the commonly used packages, e.g. Excel, MINITAB and SPSS. Formulae are kept to a minimum and relevant examples are included throughout the text.

Table of contents provided by Syndetics

• Preface (p. ix)
• Part I Statistics Basics (p. 1)
• 1 Introduction (p. 3)
• 1.1 Do you need statistics? (p. 3)
• 1.2 What is statistics? (p. 4)
• 1.3 Some important lessons I have learnt (p. 5)
• 1.4 Statistics is getting easier (p. 6)
• 1.5 Integrity in statistics (p. 7)
• 1.6 About this book (p. 8)
• 2 A Brief Tutorial on Statistics (p. 9)
• 2.1 Introduction (p. 9)
• 2.2 Variability (p. 9)
• 2.3 Samples and populations (p. 10)
• 2.4 Summary statistics (p. 11)
• 2.5 The basis of statistical tests (p. 19)
• 2.6 Limitations of statistical tests (p. 24)
• 3 Before You Start (p. 27)
• 3.1 Introduction (p. 27)
• 3.2 What statistical methods are available? (p. 28)
• 3.3 Surveys and experiments (p. 33)
• 3.4 Designing experiments and surveys - preliminaries (p. 35)
• 3.5 Summary (p. 43)
• 4 Designing an Experiment or Survey (p. 45)
• 4.1 Introduction (p. 45)
• 4.2 Sample size (p. 45)
• 4.3 Sampling (p. 50)
• 4.4 Experimental design (p. 56)
• 4.5 Further reading (p. 60)
• 5 Exploratory Data Analysis and Data Presentation (p. 63)
• 5.1 Introduction (p. 63)
• 5.2 Column graphs (p. 65)
• 5.3 Line graphs (p. 67)
• 5.4 Scatter graphs (p. 69)
• 5.5 General points about graphs (p. 71)
• 5.6 Tables (p. 73)
• 5.7 Standard errors and error bars (p. 74)
• 6 Common Assumptions or Requirements of Data for Statistical Tests (p. 77)
• 6.1 Introduction (p. 77)
• 6.2 Common assumptions (p. 81)
• 6.3 Transforming data (p. 84)
• Part II Statistical Methods (p. 91)
• 7 t-tests and F-tests (p. 93)
• 7.1 Introduction (p. 93)
• 7.2 Limitations and assumptions (p. 94)
• 7.3 t-tests (p. 95)
• 7.4 F-test (p. 103)
• 7.5 Further reading (p. 105)
• 8 Analysis of Variance (p. 107)
• 8.1 Introduction (p. 107)
• 8.2 Limitations and assumptions (p. 109)
• 8.3 One-way ANOVA (p. 111)
• 8.4 Multiway ANOVA (p. 119)
• 8.5 Further reading (p. 127)
• 9 Correlation and Regression (p. 129)
• 9.1 Introduction (p. 129)
• 9.2 Limitations and assumptions (p. 130)
• 9.3 Pearson's product moment correlation (p. 131)
• 9.4 Simple linear regression (p. 135)
• 9.5 Correlation or regression? (p. 142)
• 9.6 Multiple linear regression (p. 143)
• 9.7 Comparing two lines (p. 146)
• 9.8 Fitting curves (p. 148)
• 9.9 Further reading (p. 151)
• 10 Multivariate ANOVA (p. 153)
• 10.1 Introduction (p. 153)
• 10.2 Limitations and assumptions (p. 154)
• 10.3 Null hypothesis (p. 156)
• 10.4 Description of the test (p. 156)
• 10.5 Interpreting the results (p. 158)
• 10.6 Further reading (p. 161)
• 11 Repeated Measures (p. 163)
• 11.1 Introduction (p. 163)
• 11.2 Methods for analysing repeated measures data (p. 166)
• 11.3 Designing repeated measures experiments (p. 170)
• 11.4 Further reading (p. 170)
• 12 Chi-square Tests (p. 173)
• 12.1 Introduction (p. 173)
• 12.2 Limitations and assumptions (p. 174)
• 12.3 Goodness of fit test (p. 175)
• 12.4 Test for association between two factors (p. 178)
• 12.5 Comparing proportions (p. 181)
• 12.6 Further reading (p. 184)
• 13 Non-parametric Tests (p. 185)
• 13.1 Introduction (p. 185)
• 13.2 Limitations and assumptions (p. 188)
• 13.3 Mann-Whitney U-test (p. 189)
• 13.4 Two-sample Kolmogorov-Smirnov test (p. 191)
• 13.5 Two-sample sign test (p. 193)
• 13.6 Kruskal-Wallis test (p. 195)
• 13.7 Friedman's test (p. 198)
• 13.8 Spearman's rank correlation (p. 200)
• 13.9 Further reading (p. 203)
• 14 Principal Component Analysis (p. 205)
• 14.1 Introduction (p. 205)
• 14.2 Limitations and assumptions (p. 207)
• 14.3 Description of the method (p. 207)
• 14.4 Interpreting the results (p. 209)
• 14.5 Further reading (p. 218)
• 15 Cluster Analysis (p. 221)
• 15.1 Introduction (p. 221)
• 15.2 Limitations and assumptions (p. 222)
• 15.3 Clustering observations (p. 223)
• 15.4 Clustering variables (p. 226)
• 15.5 Further reading (p. 228)
• Appendices (p. 229)
• A Calculations for statistical tests (p. 231)
• B Concentration data for Chapters 14 and 15 (p. 247)
• C Using computer packages (p. 249)
• D Choosing a test: decision table (p. 261)
• E List of worked examples (p. 265)
• Bibliography (p. 271)
• Index (p. 273)

Author notes provided by Syndetics

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