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Environmental statistics with S-Plus / Steven P. Millard, Nagaraj K. Neerchal.

LIBRA GE45.S73 M55 2001
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Format:
Book
Author/Creator:
Millard, Steven P.
Contributor:
Neerchal, Nagaraj K.
Series:
Applied environmental statistics
Language:
English
Subjects (All):
Environmental sciences--Statistical methods--Data processing.
Environmental sciences.
S-Plus.
Environmental sciences--Statistical methods.
Physical Description:
830 pages : illustrations ; 24 cm.
Other Title:
Environmental statistics
Place of Publication:
Boca Raton : CRC Press, [2001]
Summary:
The combination of easy-to-use software with easy access to a description of the statistical methods (definitions, concepts, etc.) makes this book an excellent resource. One of the major features of this book is the inclusion of general information on environmental statistical methods and examples of how to implement these methods using the statistical software package S-Plus and the add-in modules EnvironmentalStats for S-Plus, S+SpatialStats, and S-Plus for ArcView.
Contents:
Environmental Science, Regulations, and Statistics 2
Data Sets and Case Studies 10
Software 11
2 Designing a Sampling Program, Part I 13
The Basic Scientific Method 13
What is a Population and What is a Sample? 15
Random vs. Judgment Sampling 15
The Hypothesis Testing Framework 16
Common Mistakes in Environmental Studies 17
The Data Quality Objectives Process 19
Sources of Variability and Independence 24
Methods of Random Sampling 26
3 Looking at Data 53
Summary Statistics 53
Graphs for a Single Variable 67
Graphs for Two or More Variables 113
4 Probability Distributions 139
What is a Random Variable? 139
Discrete vs. Continuous Random Variable 140
What is a Probability Distribution? 141
Probability Density Function (PDF) 145
Cumulative Distribution Function (CDF) 153
Quantiles and Percentiles 158
Generating Random Numbers from Probability Distributions 161
Characteristics of Probability Distributions 162
Important Distributions in Environmental Statistics 167
Multivariate Probability Distributions 194
5 Estimating Distribution Parameters and Quantiles 201
Methods for Estimating Distribution Parameters 201
Using EnvironmentalStats for S-Plus to Estimate Distribution Parameters 215
Comparing Different Estimators 219
Accuracy, Bias, Mean Square Error, Precision, Random Error, Systematic Error, and Variability 225
Parametric Confidence Intervals for Distribution Parameters 228
Nonparametric Confidence Intervals Based on Bootstrapping 257
Estimates and Confidence Intervals for Distribution Quantiles (Percentiles) 274
A Cautionary Note about Confidence Intervals 289
6 Prediction Intervals, Tolerance Intervals, and Control Charts 295
Prediction Intervals 296
Simultaneous Prediction Intervals 320
Tolerance Intervals 335
Control Charts 353
7 Hypothesis Tests 365
The Hypothesis Testing Framework 365
Overview of Univariate Hypothesis Tests 371
Goodness-of-Fit Tests 371
Test of a Single Proportion 385
Tests of Location 389
Tests on Percentiles 409
Tests on Variability 410
Comparing Locations between Two Groups: The Special Case of Paired Differences 412
Comparing Locations between Two Groups 415
Comparing Two Proportions 441
Comparing Variances between Two Groups 446
The Multiple Comparisons Problem 450
Comparing Locations between Several Groups 453
Comparing Proportions between Several Groups 461
Comparing Variability between Several Groups 462
8 Designing a Sampling Program, Part II 471
Designs Based on Confidence Intervals 471
Designs Based on Nonparametric Confidence, Prediction, and Tolerance Intervals 481
Designs Based on Hypothesis Tests 485
Optimizing a Design Based on Cost Considerations 521
9 Linear Models 527
Covariance and Correlation 527
Simple Linear Regression 539
Regression Diagnostics 553
Calibration, Inverse Regression, and Detection Limits 562
Multiple Regression 575
Dose-Response Models: Regression for Binary Outcomes 584
Other Topics in Regression 588
10 Censored Data 593
Classification of Censored Data 593
Graphical Assessment of Censored Data 597
Estimating Distribution Parameters 609
Estimating Distribution Quantiles 636
Prediction and Tolerance Intervals 637
Hypothesis Tests 640
A Note about Zero-Modified Distributions 645
11 Time Series Analysis 647
Creating and Plotting Time Series Data 647
Autocorrelation 651
Dealing with Autocorrelation 669
More Complicated Models: Autoregressive and Moving Average Processes 671
Estimating and Testing for Trend 672
12 Spatial Statistics 693
Overview: Types of Spatial Data 693
The Benthic Data 694
Models for Geostatistical Data 700
Modeling Spatial Correlation 703
Prediction for Geostatistical Data 721
Using S-Plus for ArcView GIS 727
13 Monte Carlo Simulation and Risk Assessment 735
Monte Carlo Simulation 736
Generating Random Numbers 741
Uncertainty and Sensitivity Analysis 748
Risk Assessment 758.
Notes:
Includes bibliographical references (pages 779-816) and index.
ISBN:
0849371686
OCLC:
44550619

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