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Likelihood Methods in Biology and Ecology: A Modern Approach to Statistics emphasizes the importance of the likelihood function in statistical theory and applications and discusses it in the context of biology and ecology. Bayesian and frequentist methods both use the likelihood function and provide differing but related insights. This is examined here both through review of basic methodology and also the integrated use of these approaches in case studies.
- Discusses the likelihood function in both Bayesian and frequentist contexts.
- Reviews and discusses standard methods of data analysis, model selection and statistical analysis, and how to apply and interpret them in real world situations.
- Examines the application of statistical methods to observed data in the context of case studies drawn from biology and ecology.
- Uniquely discusses frequentist and Bayesian approaches to statistics as complementary allowing many standard approaches to be presented in a single book.
- Poses questions to ask when planning the design and analysis of a study or experiment.
Likelihood Methods in Biology and Ecology is written for applied researchers, scientists, consultants, statisticians and applied scientists. Although it uses examples drawn from biology, the methods here can be applied to a wide variety of research areas and provides an accessible handbook of available statistical methods for scientific settings where there is an assumed theoretical model that can be represented using a likelihood function.
1. Statistical Models in Scientific Research
II Basic Tools for Data Analysis, Study Design and Model Development
2. Data Analysis and Patterns
3. Some Basic Concepts in the Design of Experiments
4. Prior Beliefs and Basic Statistical Models
III Likelihood Based Statistical Theory and Methods:Frequentist and Bayesian
5. Introduction to Frequentist Likelihood Based Statistical Theory
6. Introduction to Bayesian Statistical Methods
IV Applications Using Bayesian and Frequentist Likelihood Methods in Biology and Ecology
7. Case Studies: Bayesian and Frequentist Perspectives
8. Biodiversity: Modeling Species Abundance
9. Soil Erosion in Relation to Season and Land Usage Patterns
10. Immunity and Dose Response in Relation to Aquaculture
11. Patterns of Genetic Expression in Mouse Liver Cancer
12. Antibiotic Resistance in Relation to Genetic Patterns in Tuberculosis