| Description |
1 online resource (177 pages) |
| Series |
Statistics: A Series of Textbooks and Monographs |
|
Statistics, textbooks and monographs.
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| Contents |
Intro; Halftitle Page; Title Page; Copyright; Dedication; Table of Contents; Preface; PART 1 I Introduction; 1 Statistical Models in Scientific Research; 1.1 Statistics in Science; 1.1.1 Guidelines to Statistical Model Building; 1.1.2 Questions and Answers; 1.1.3 Basic Statistical Models; 1.1.4 Likelihood Function; 1.1.5 Frequentist Interpretation; 1.2 Bayesian Statistical Analysis and Interpretation; 1.3 A Comparative and Practically Integrated Approach; 1.4 Computing; 1.5 Bibliography; 1.6 Suggested Readings; PART 2 II Basic Tools for Data Analysis, Study Design and Model Development |
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2 Data Analysis and Patterns2.1 Data Analysis, Beliefs, and Statistical Models; 2.2 Basic Graphical and Visualization Tools; 2.3 Data in One-Dimension; 2.3.1 Example 1; 2.3.2 Example 2; 2.4 Data Patterns in Higher Dimensions: Correlationsand Associations; 2.4.1 Example 3; 2.5 Principal Components Analysis; 3 Some Basic Concepts in the Design of Experiments; 3.1 Design of Experiments and Data Collection; 3.1.1 Simpson's Paradox; 3.1.1.1 Example 1; 3.1.1.2 Example 2; 3.1.1.3 Path Analysis; 3.1.2 Replication in the Design and Analysis of Experiments; 3.1.2.1 Replication and Modeling |
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3.1.2.2 Fully Replicated Design in Single Overall Model3.1.2.3 Significance Issues; 3.1.2.4 Pseudo-Replication in Observational Studies; 3.1.2.5 Replication and Meta-Analysis; 3.1.3 Incorporating Expectations and Beliefs; 4 Prior Beliefs and Basic Statistical Models; 4.1 Selecting Prior Densities; 4.1.1 Subjective Priors; 4.1.2 Previous Likelihoods: A Source of Prior Information; 4.1.3 Jeffreys Prior; 4.1.4 Non-Informative and Improper Priors; 4.1.5 Conjugate Priors; 4.1.6 Reference Priors; 4.1.7 Elicitation; 4.2 Model Nonlinearity and Prior Selection; 4.2.1 Example 4: BOD Example |
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4.2.2 Example 5: Whale Population Dynamics Example4.3 Selecting Parametric Models and Likelihoods; 4.4 Bibliography; 4.5 Questions; 4.6 Suggested Readings; PART 3 III Likelihood Based Statistical Theory and Methods: Frequentist and Bayesian; 5 Introduction to Frequentist Likelihood Based Statistical Theory; 5.1 Statistical Theory Related to Likelihoods; 5.1.1 Example: Normal Distribution; 5.2 Basic Statistical Models; 5.2.1 T-Test; 5.2.2 Anova; 5.2.3 More on Linear Models; 5.2.4 Centering and Interaction Effects in Linear Models; 5.2.4.1 Example: Penrose Bodyfat |
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5.2.5 High-Dimensional Linear Models5.2.5.1 Ridge Regression; 5.2.6 Generalized Linear Models; 5.2.7 Random Effects; 5.2.8 Nonlinear Models; 5.2.9 Model Mis-Specification: Nonlinearity; 5.2.10 Introduction to Basic Survival Analysis; 5.2.10.1 Survival Analysis Modeling; 5.2.10.2 Linear Models in Survival Analysis; 5.2.10.3 Random Effects in Survival Settings; 5.2.10.4 Comparisons to Standard Methods; 5.3 Estimation and Testing; 5.3.1 Assessing Significance; 5.3.1.1 Generic Bootstrap Procedure; 6 Introduction to Bayesian Statistical Methods |
| Summary |
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 |
| Notes |
6.1 Bayesian Approach to Statistical Modeling and Inference |
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Print version record |
| Subject |
Ecology -- Statistical methods
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Biometry.
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Biometry
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biometrics.
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NATURE -- Ecology.
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Biometry
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Ecology -- Statistical methods
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| Form |
Electronic book
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| ISBN |
9780429533235 |
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0429533233 |
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