Water Supply and Quality Book from C.H.I.P.S.

Statistical Methods for Groundwater Monitoring
Second Edition by Robert D. Gibbons
Statistical Methods for Groundwater Monitoring explores quantitative concepts useful for surface water monitoring as well as soil and air monitoring applications while also maintaining a focus on the analysis of groundwater monitoring data in order to detect environmental impacts from a variety of sources, such as industrial activity and waste disposal.
Features:
 An introduction to Intralaboratory Calibration Curves and randomeffects regression models for nonconstant measurement variability
 Coverage of statistical prediction limits for a gammadistributed random variable, with a focus on estimation and testing of parameters in environmental monitoring applications
 A unified treatment of censored data with the computation of statistical prediction, tolerance, and control limits
 Expanded coverage of statistical issues related to laboratory practice, such as detection and quantitation limits
Each chapter provides a general overview of a problem, followed by statistical derivation of the solution and a relevant example complete with computational details that allow readers to perform routine application of the statistical results.
Relevant issues are highlighted throughout, and recommendations are also provided for specific problems based on characteristics such as number of monitoring wells, number of constituents, distributional form of measurements, and detection frequency.
Contents
1. Normal Prediction Intervals
 Prediction Intervals for the Next Single Measurement from a Normal Distribution
 Prediction Limits for the Next k Measurements from a Normal Distribution
 Normal Prediction Limits with Resampling
 Simultaneous Normal Prediction Limits for the Next k Samples
 Simultaneous Normal Prediction Limits for the Next r of m Measurements at Each of k Monitoring Wells
 Normal Prediction Limits for the Mean(s) of m > 1 Future Measurements at Each of k Monitoring Wells
2. Nonparametric Prediction Intervals
 Pass 1 of m Samples
 Pass m  1 of m Samples
 Pass First or all m  1 Resamples
 Nonparametric Prediction Limits for the Median of m Future Measurements at each of k Locations
3. Prediction Intervals for Other Distributions
 Lognormal Distribution
 Lognormal Prediction Limits for the Median of m Future Measurements
 Lognormal Prediction Limits for the Mean of m Future Measurements
 Poisson Distribution
4. Gamma Prediction Intervals and Some Related Topics
 Gamma Distribution
 Comparison of Gamma mean to a Regulatory Standard
5. Tolerance Intervals
 Normal Tolerance Limits
 Poisson Tolerance Limits
 Gamma Tolerance Limits
 Nonparametric Tolerance Limits
6. Method Detection Limits
 Single Concentration Designs
 Calibration Designs
7. Practical Quantitation Limits
 Operational Definition
 A Statistical Estimate of the PQL
 Derivation of the PQL
 A Simpler Alternative
 Uncertainty
 The Effect of the Transformation
 Selecting N
8. Interlaboratory Calibration
 General Random Effects Regression Model for the Case of Heteroscedastic Measurement Errors
 Estimation of Model Parameters
 Applications of the Derived Results
9. Contaminant Source Analysis
 Statistical Classification Problems
 Nonparametric Methods
10. IntraWell Comparison
 Shewart Control Charts
 (CUSUM) Control Charts
 Combined ShewartCUSUM Control Charts
 Prediction Limits
 Pooling Variance Estimates
11. Trend Analysis
 Sen Test
 MannKendall Test
 Seasonal Kendall Test
 Some Statistical Properties
12. Censored Data
 Conceptual Foundation
 Simple Substitution Methods
 Maximum Likelihood Estimators
 Restricted Maximum Likelihood Estimators
 Linear Estimators
 Alternative Linear Estimators
 Delta Distributions
 Regression Methods
 Substitution of Expected Values of Order Statistics
 Comparison of Estimators
 Some Simulation Results
13. Normal Prediciton Limits for LeftCensored Data
 Prediction Limit for LeftCensored Normal Data
 Simulation Study
14. Tests for Departure from Normality
 A Simple Graphical Approach
 The ShapiroWilk Test
 ShapiroFrancia Test
 D'Agostino Test
 Methods Based on Moments of a Normal Distribution
 Multiple Independent Samples
 Testing Normality in Censored Samples
 The KolmogorovSmirnov Test
15. Variance Component Models
 LeastSquares Estimators
 Maximum Likelihood Estimators
16. Detecting Outliers
 Rosner Test
 Skewness Test
 Kurtosis Test
 ShapiroWilk Test
 Em statistic
 Dixon Test
17. Surface Water Analysis
 Statistical Considerations
 Statistical Power
18. Assessment and Corrective Action Monitoring
 Strategy
 LCL or UCL?
 Normal Confidence Limits for the Mean
 Lognormal Confidence Limits for the Median
 Lognormal Confidence Limits for the Mean
 Nonparametric Confidence Limits for the Median
 Confidence Limits for Other Percentiles of the Distribution
19. Regulatory Issues
 Regulatory Statistics
 Methods to be Avoided
 Verification Resampling
 Interwell versus Intrawell Comparisons
 Computer Software
 More Recent Developments
Index
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Statistical Methods for Groundwater Monitoring
Second Edition by Robert D. Gibbons
2009 • 374 pages • $114.00 + shipping
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