Book contents
- Frontmatter
- Contents
- Preface
- 1 Statistical analysis in behavioral ecology
- 2 Estimation
- 3 Tests and confidence intervals
- 4 Survey sampling methods
- 5 Regression
- 6 Pseudoreplication
- 7 Sampling behavior
- 8 Monitoring abundance
- 9 Capture–recapture methods
- 10 Estimating survivorship
- 11 Resource selection
- 12 Other statistical methods
- APPENDIX ONE Frequently used statistical methods
- APPENDIX TWO Statistical tables
- APPENDIX THREE Notes for Appendix One
- References
- Index
12 - Other statistical methods
Published online by Cambridge University Press: 04 December 2009
- Frontmatter
- Contents
- Preface
- 1 Statistical analysis in behavioral ecology
- 2 Estimation
- 3 Tests and confidence intervals
- 4 Survey sampling methods
- 5 Regression
- 6 Pseudoreplication
- 7 Sampling behavior
- 8 Monitoring abundance
- 9 Capture–recapture methods
- 10 Estimating survivorship
- 11 Resource selection
- 12 Other statistical methods
- APPENDIX ONE Frequently used statistical methods
- APPENDIX TWO Statistical tables
- APPENDIX THREE Notes for Appendix One
- References
- Index
Summary
Introduction
Several statistical methods not previously discussed are briefly described in this Chapter. Our goal is to introduce the methods and indicate where more information on them may be found rather than to present in-depth discussions of the techniques. The first three Sections discuss relatively new methods that have not been widely used in behavioral ecology, or at least some of its subdisciplines, but that may be useful in a variety of applications. The subsequent three Sections discuss other branches of statistics with well-developed methods that we have not had space in this book to cover in detail.
Adaptive sampling
In conventional survey sampling plans, such as those discussed in Chapter Four, the sampling plan and sample size are determined before collecting the data and, in theory, all of the population units to be included in the sample could be identified before data collection begins. This approach, however, is sometimes unsatisfactory when the population units are uncommon and clumped in space and/or time. For example, suppose we are estimating the proportion of trees in an orchard damaged by rodents, and the damage occurs in widely scattered patches. We select rows of trees to inspect. Most trees are undamaged but occasionally we encounter an area in which most trees are damaged. Under conventional sampling plans we can only include trees in the selected rows in our sample. Yet we may be able to see that the damage extends to nearby rows and feel that some way should exist to include those trees in the sample as well.
- Type
- Chapter
- Information
- Sampling and Statistical Methods for Behavioral Ecologists , pp. 248 - 256Publisher: Cambridge University PressPrint publication year: 1998