Book contents
- Frontmatter
- Contents
- Preface
- 1 Introduction
- 2 “Doing science”: hypotheses, experiments and disproof
- 3 Collecting and displaying data
- 4 Introductory concepts of experimental design
- 5 Doing science responsibly and ethically
- 6 Probability helps you make a decision about your results
- 7 Working from samples: data, populations and statistics
- 8 Normal distributions: tests for comparing the means of one and two samples
- 9 Type 1 and Type 2 error, power and sample size
- 10 Single-factor analysis of variance
- 11 Multiple comparisons after ANOVA
- 12 Two-factor analysis of variance
- 13 Important assumptions of analysis of variance, transformations and a test for equality of variances
- 14 Two-factor analysis of variance without replication, and nested analysis of variance
- 15 Relationships between variables: linear correlation and linear regression
- 16 Linear regression
- 17 Non-parametric statistics
- 18 Non-parametric tests for nominal scale data
- 19 Non-parametric tests for ratio, interval or ordinal scale data
- 20 Introductory concepts of multivariate analysis
- 21 Introductory concepts of sequence analysis
- 22 Introductory concepts of spatial analysis
- 23 Choosing a test
- Appendices
- References
- Index
Appendices
Published online by Cambridge University Press: 05 June 2012
Book contents
- Frontmatter
- Contents
- Preface
- 1 Introduction
- 2 “Doing science”: hypotheses, experiments and disproof
- 3 Collecting and displaying data
- 4 Introductory concepts of experimental design
- 5 Doing science responsibly and ethically
- 6 Probability helps you make a decision about your results
- 7 Working from samples: data, populations and statistics
- 8 Normal distributions: tests for comparing the means of one and two samples
- 9 Type 1 and Type 2 error, power and sample size
- 10 Single-factor analysis of variance
- 11 Multiple comparisons after ANOVA
- 12 Two-factor analysis of variance
- 13 Important assumptions of analysis of variance, transformations and a test for equality of variances
- 14 Two-factor analysis of variance without replication, and nested analysis of variance
- 15 Relationships between variables: linear correlation and linear regression
- 16 Linear regression
- 17 Non-parametric statistics
- 18 Non-parametric tests for nominal scale data
- 19 Non-parametric tests for ratio, interval or ordinal scale data
- 20 Introductory concepts of multivariate analysis
- 21 Introductory concepts of sequence analysis
- 22 Introductory concepts of spatial analysis
- 23 Choosing a test
- Appendices
- References
- Index
- Type
- Chapter
- Information
- Geostatistics ExplainedAn Introductory Guide for Earth ScientistsPublisher: Cambridge University PressPrint publication year: 2010