Environmental Statistics with S-PLUS: 1st Edition (Hardback) book cover

Environmental Statistics with S-PLUS

1st Edition

By Steven P. Millard, Nagaraj K. Neerchal

CRC Press

848 pages

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pub: 2000-09-21
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Description

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.

Reviews

"… a comprehensive resource for environmental scientists, engineers, regulators, and students who need to collect and make sense of environmental data. …A strong feature of the text is the companion information and datasets posted on the book's website. …The book is a good general text in statistical methodology that addresses the use of S-Plus."

-JASA, September 2001

"…provides an exhaustive treatment of the statistical sampling and analysis issues that confront applied environmental statisticians and scientists. Drs. Millard and Neerchal have a rare talent for explaining and illustrating even the most difficult statistical procedures and principles in language that is clear and free of jargon. However, the most unique feature of the software and text is that they are seamlessly interwoven, each complimenting the other. The software illustrates the book and the book places the software in the context of the underlying environmental research questions. This is unprecedented. Together the software and the book clarify the DQO and DQA process to such an extent that it is hard for me to imagine applying these principles to my own work or teaching them to applied scientists without the two."

-Michael Riggs, RTI

"The combination of easy-to-use software with easy access to a description of statistical methods is done with thoroughness and skill."

-Richard Gilbert, Battelle Pacific NW Labs

"Environmental Statistics with S-PLUS is a textbook with a thorough coverage of basic data analysis, but it also ventures into more complex areas such as risk assessment and spatial statistics. Although the use of the relevant S-PLUS packages is described throughout, the book is basically about statistics, not software: It is statistics 'with' rather than 'in' or 'for' S-PLUS. It is intended for just about anyone: in practice it would be suitable for many people with a background in engineering or environmental health."

-Technometrics, Vol. 43, No. 4, November 2001

Table of Contents

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.

About the Series

Chapman & Hall/CRC Applied Environmental Statistics

Learn more…

Subject Categories

BISAC Subject Codes/Headings:
MAT029000
MATHEMATICS / Probability & Statistics / General
SCI013000
SCIENCE / Chemistry / General
SCI026000
SCIENCE / Environmental Science