Introduction -- Statistical models in scientific research -- Basic tools for data analysis, study design and model development -- Data analysis and patterns -- Some basic concepts in the design of experiments -- Prior beliefs and basic statistical models -- Likelihood based statistical theory and methods : frequentist and bayesian -- Introduction to frequentist likelihood based statistical theory -- Introduction to bayesian statistical methods -- Applications using bayesian and frequentist likelihood methods in biology and ecology -- Case studies: baysesian and frequentist perspectives -- Case studies in ecology -- Soil erosion in relation to season and land usage patterns -- Case studies in biology -- Patterns of genetic expression in mouse liver cancer -- Antibiotic resistance in relation to genetic patterns in tuberculosis -- Index.
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SUMMARY OR ABSTRACT
Text of Note
This book 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. This book 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.