Statistics for Environmental Biology and Toxicology

1. Auflage 1997
ISBN: 978-0-412-04731-2
Verlag: Chapman and Hall/CRC

Buch, Englisch, 596 Seiten, Format (B × H): 161 mm x 239 mm, Gewicht: 1260 g

Reihe: Chapman & Hall/CRC Interdisciplinary Statistics

Statistics for Environmental Biology and Toxicology presents and illustrates statistical methods appropriate for the analysis of environmental data obtained in biological or toxicological experiments. Beginning with basic probability and statistical inferences, this text progresses through non-linear and generalized linear models, trend testing, time-to-event data and analysis of cross-classified tabular and categorical data. For the more complex analyses, extensive examples including SAS and S-PLUS programming code are provided to assist the reader when implementing the methods in practice.

Zielgruppe

Professional

Autoren/Hrsg.

Bailer, A. John

Piegorsch, Walter.

Fachgebiete

• Mathematik | Informatik Mathematik Stochastik Mathematische Statistik
• Geowissenschaften Umweltwissenschaften Umweltüberwachung, Umweltanalytik, Umweltinformatik
• Mathematik | Informatik Mathematik Stochastik Wahrscheinlichkeitsrechnung
• Geowissenschaften Umweltwissenschaften Angewandte Ökologie
• Geowissenschaften Umweltwissenschaften Umwelttechnik
• Technische Wissenschaften Umwelttechnik | Umwelttechnologie Umwelttechnik

Inhaltsverzeichnis

Basic Probability and Statistical Distributions, Introductory Concepts in Probability, Families of Discrete Distributions, Families of Continuous Distributions, The Exponential Class, Families of Multivariate Distributions, Summary, Exercises, Fundamentals of Statistical Inference, Introductory Concepts in Statistical Estimation, Nature and Properties of Estimators, Techniques for Constructing Statistical Estimators, Statistical Inference - Testing Hypotheses, Statistical Inference - Confidence Intervals, Confidence Intervals for Some Special Distributions, Semi-Parametric Inference, Summary, Exercises, Fundamental Issues in Experiment Design, Basic Terminology in Experiment Design, The Experimental Unit, Random Sampling and Randomization, Sample Sizes and Optimal Animal Allocation, Dose Selection, Summary, Exercises, Data Analysis of Treatment versus Control Differences, Two-Sample Comparisons - Testing Hypotheses, Two-Sample Comparisons - Confidence Intervals, Summary, Exercises, Treatment-versus-Control Multiple Comparisons, Comparing More than Two Populations, Multiple Comparisons via Bonferroni's Inequality, Multiple Comparisons among a Control - Normal Sampling, Multiple Comparisons among Binomial Populations, Multiple Comparisons with a Control - Poisson Samling, All-Pairwise Multiple Comparisons, Summary, Exercises, Trend Testing, Simple Linear Regression for Normal Data, William's Test for Normal Data, Trend Tests for Proportions, Cochran-Armitage Trend Test for Counts, Overdispersed Discrete Data, Distribution-Free Trend Testing, Nonparametric Tests for Nonmonotone (Umbrella) Trends, Summary, Exercises, Dose-Response Modeling and Analysis, Dose-Response Models on a Continuous Scale, Dose-Response Models on a Discrete Scale, Potency Estimation for Dose-Response Data, Comparing Dose-Response Curves, Summary, Exercises, Introduction to Gener

Über Autor(innen)

Walter W. Piegorsch is Professor of Statistics at the University of South Carolina, Columbia, SC, USA. A. John Bailer is Professor of Mathematics and Statistics and Co-director of the Center for Environmental Toxicology and Statistics at Miami University, Oxford, OH, USA.