Millard / Neerchal / Dixon Environmental Statistics with S-PLUS

1. Auflage 2010
ISBN: 978-1-4200-3717-3
Verlag: Taylor & Francis
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 848 Seiten

Reihe: Chapman & Hall/CRC Applied Environmental Statistics

A clear, comprehensive treatment of the subject, Environmental Statistics with S-PLUS surveys the vast array of statistical methods used to collect and analyze environmental data. The book explains what these methods are, how to use them, and where to find references to them. In addition, it provides insight into what to think about before you collect environmental data, how to collect the data, and how to make sense of it after collection.

A unique and powerful feature of the book is its integration with the commercially available software package S-Plus and the add-on modules EnvironmentalStats for S-PLUS, S+SpatialStats, and S-PLUS for ArcView. The book presents data sets to explain statistical methods, and then shows how to implement these methods by providing the commands for and the results from the software.

This survey of statistical methods, definitions, and concepts helps you collect and effectively analyze data for environmental pollution problems. Using the S-PLUS software in conjunction with this text will no doubt increase understanding of the methods.

Zielgruppe

Environmental scientists, engineers, and regulators, and students taking courses in environmental statistics, statistics, biostatistics, and environmental science.

Autoren/Hrsg.

Millard, Steven P.

Neerchal, Nagaraj K.

Dixon, Philip

Fachgebiete

• Technische Wissenschaften Umwelttechnik | Umwelttechnologie Umwelttechnik
• Mathematik | Informatik Mathematik Stochastik Mathematische Statistik
• Geowissenschaften Umweltwissenschaften Umweltüberwachung, Umweltanalytik, Umweltinformatik
• Mathematik | Informatik EDV | Informatik Business Application Mathematische & Statistische Software
• Mathematik | Informatik Mathematik Stochastik Wahrscheinlichkeitsrechnung

Inhaltsverzeichnis

INTRODUCTION
Intended Audience
Environmental Science, Regulations, and Statistics

Overview

Data Sets and Case Studies

Software

DESIGNING A SAMPLING PROGRAM, PART I
The Basic Scientific Method

What is a Population and What Is a Sample?

Random vs. Judgment Sampling

The Hypothesis Testing Framework

Common Mistakes in Environmental Studies
The Data Quality Objectives Process

Sources of Variability and Independence

Methods of Random Sampling

Case Study

LOOKING AT DATA
Summary Statistics

Graphs for a Single Variable

Graphs for Two or More Variables

PROBABILITY DISTRIBUTIONS
What Is a Random Variable?

Discrete vs. Continuous Random Variable

What is a Probability Distribution?

Probability Density Function (PDF)
Cumulative Distribution Function (CDF)

Quantiles and Percentiles

Generating Random Numbers from Probability Distributions

Characteristics of Probability Distributions

Important Distributions in Environmental Statistics

Multivariate Probability Distributions

ESTIMATING DISTRIBUTION PARAMETERS AND QUANTILES
Methods for Estimating Distribution Parameters

Using EnvironmentalStats for S?Plus to Estimate Distribution Parameters

Comparing Different Estimators

Accuracy, Bias, Mean Square Error, Precision, Random Error, Systematic Error, and Variability
Parametric Confidence Intervals for Distribution Parameters

Nonparametric Confidence Intervals Based on Bootstrapping

Estimates and Confidence Intervals for Distribution Quantiles (Percentiles)

A Cautionary Note about Confidence Intervals

PREDICTION INTERVALS, TOLERANCE INTERVALS, AND CONTROL CHARTS
Prediction Intervals

Simultaneous Prediction Intervals

Tolerance Intervals

Control Charts

HYPOTHESIS TESTS
The Hypothesis Testing Framework
Overview of Univariate Hypothesis Tests

Goodness-of-Fit Tests

Test of a Single Proportion

Tests of Location

Tests on Percentiles

Tests on Variability

Comparing Locations between Two Groups: The Special Case of Paired Differences

Comparing Locations between Two Groups

Comparing Two Proportions

Comparing Variances between Two Groups

The Multiple Comparisons Problem

Comparing Locations between Several Groups

Comparing Proportions between Several Groups

Comparing Variability between Several Groups

DESIGNING A SAMPLING PROGRAM, PART II
Designs Based on Confidence Intervals
Designs Based on Nonparametric Confidence, Prediction, and Tolerance Intervals

Designs Based on Hypothesis Tests

Optimizing a Design Based on Cost Considerations

LINEAR MODELS
Covariance and Correlation

Simple Linear Regression

Regression Diagnostics

Calibration, Inverse Regression, and Detection Limits

Multiple Regression

Dose-Response Models: Regression for Binary Outcomes

Other Topics in Regression

CENSORED DATA
Classification of Censored Data

Graphical Assessment of Censored Data

Estimating Distribution Parameters

Estimating Distribution Quantiles

Prediction and Tolerance Intervals

Hypothesis Tests

A Note about Zero-Modified Distributions

TIME SERIES ANALYSIS
Creating and Plotting Time Series Data

Autocorrelation

Dealing with Autocorrelation

More Complicated Models: Autoregressive and Moving Average Processes

Estimating and Testing for Trend

SPATIAL STATISTICS
Overview: Types of Spatial Data

The Benthic Data

Models for Geostatistical Data

Modeling Spatial Correlation

Prediction for Geostatistical Data
Using S-Plus for ArcView GIS

MONTE CARLO SIMULATION AND RISK ASSESSMENT
Overview

Monte Carlo Simulation

Generating Random Numbers

Uncertainty and Sensitivity Analysis

Risk Assessment

REFERENCES

INDEX

Summaries and Exercises appear at the end of each chapter.