Statistics for environmental biology and toxicology
著者
書誌事項
Statistics for environmental biology and toxicology
(Interdisciplinary statistics)
Chapman & Hall, 1997
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内容説明・目次
内容説明
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.
目次
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 Generalized Linear Models
(GLiMs)
Review of Classical Linear Models
Generalizing the Classical Linear Model
Generalized Linear Models
Examples and Illustrations
Summary
Exercises
Analysis of Cross-Classified Tabular/Categorical Data
RxC Contingency Tables
Statistical Distributions for Categorical Data
Statistical Tests of Independence in RxC Tables
Log-Linear Models and Relationships to GLiMs
Tables of Proportions
Summary
Exercises
Incorporating Historical Control Information
Guidelines for Using Historical Control Data
Two-Sample Hypothesis Testing - Normal Distribution Sampling
Two-Sample Hypothesis Testing - Binomial Sampling
Trend Testing with Historical Controls
Summary
Exercises
Survival Data Analysis
Survival Data
Lifetime Distributions
Estimating the Survivor Function
Nonparametric Methods for Comparing Survival Curves
Regression Models for Survival Data
Summary
Exercises
Appendices
References
「Nielsen BookData」 より