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Researched 4 December 2000
* Updated 16 January 2001
** Updated 2 February 2001
*** Updated 4 April 2001
§ Updated 7 May 2001
| Page | Description | Updated |
| Crystal Ball | Stochastic simulation (Monte-Carlo) add-on for Excel | 3 March 01 |
| @Risk | Stochastic simulation (Monte-Carlo) add-on for Excel | 3 March 01 |
Many of these references are on reserve (for one week signout) at the Great Valley library. Follow the library page's links for the electronic reserves for this course. These contain scanned versions of selected reference material, available only to qualified Penn State accounts.
This list of references is far from complete: it is intended to supplement the bibliography in the text by providing additional references or expanded descriptions of references already in the bibliography. The stars (*) may help you prioritize your researches, as follows:
(***) A must read.
(**) You should at least have this on your shelf.
(*) A specialized text: it if matches your interest, needs, or abilities, then treat it as a two-star book.
Some references appear under more than one heading and may have different star ratings depending on their appropriateness to that heading.
Beyer, William, Ed., CRC Handbook of Tables for Probability and Statistics. 1968, CRC Press, Boca Raton. ISBN 0-8493-0692-2. Useful for quick calculations, checking software, and for the tables of random numbers.
*** Freedman, David, et al., Statistics (Second Edition). 1991, W. W. Norton, New York. ISBN 0-393-96043-9. Exceptionally readable introduction to statistical thinking. Based on extensive and interesting examples. Non-mathematical: performs all calculations with graphics and tables. Excellent discussion of the non-mathematical aspects of sampling, such as the need for a probability model, randomization, and controls.
** Lehr, Jay H., ed., Standard Handbook of Environmental Science, Health, and Technology. 2000, McGraw-Hill, New York. ISBN 0-07-038309-X. Twenty-two chapters (about 1500 pages) on almost everything, ranging from chemistry through environmental science in the legal system. Includes sections on geostatistics, variability and uncertainty, and decision analysis.
Manly, Bryan F. J., Statistics for Environmental Science and Management. 2001, Chapman & Hall/CRC Press, Boca Raton. ISBN 1-58488-029-5. Attempts to cover much of the same material as Millard & Neerchal, but concentrates specifically on statistical procedures. There is no place in this text for exploratory data analysis. It contains no exercises. It is intended as a "reference" but is written and organized like a textbook. Close in form to a statistical "cookbook", it is notable mainly for its currency and for the large variety of techniques discussed. However, it is woefully incomplete. For example, consider the lognormal distribution, which has been of enormous importance in environmental data analysis for two decades. This book devotes less than a page to this distribution. It provides the pdf and the expected value and variance (without a derivation), but then (as far as I can see) never uses this distribution again. You cannot even find a reference to it in the index!
* Morrison, Robert, Environmental Forensics: Principles & Applications. 2000, CRC Press, Boca Raton. ISBN 0-8493-2058-5. Assembles, in one place, background in the chemistry, transport, and fate of environmental contaminants. Especially noteworthy is the attention to detail, regardless of what specialty is involved: you will find descriptions and photographs of sample collection procedures as well as the partial differential equations for contaminant transport in various media. The last chapter discusses some aspects of data presentation and analysis for "environmental trial exhibits." However, the level of the book lurches unpredictably from elementary to highly condensed technical material. It may allocate only a single paragraph to an entire subject area (kriging gets three paragraphs) or a whole section to trivialities (an enumeration of sample documentation, with little comment, occupies seven pages). It is likely to be most useful to a newcomer to environmental investigation, to see what traps and pitfalls may lie ahead, and to the experienced consultant, who will be able to read the book critically and overlook its shortcomings.
** Paulos, John Allen, Innumeracy: Mathematical Illiteracy and its Consequences. 1988 (Vintage Books Edition 1990, paperback, ISBN 0-679-72601-2.) A popular book, non-technical, aimed at characterizing "innumeracy" through copious simple examples. There is a heavy weighting on probability and statistics.
** Stuart, Alan and J. Keith Ord, Kendall's Advanced Theory of Statistics. Fifth Edition, Volume 1: Distribution Theory. 1987, Oxford University Press, New York. ISBN 0-19-520561-8. A standard reference on probability distributions, sampling distributions, and statistics. Very useful for understanding the basis of derivations and terminology appearing in other works and for checking their accuracy. Written at an introductory graduate level, with many exercises (but no solutions), this text nevertheless avoids the abstract theory of measure and integration, but focuses on practical and applicable techniques.
** USEPA, Guidance for the Data Quality Objectives Process. 1994, EPA QA/G-4.
* Hoaglin, David C., F. Mosteller, and J. Tukey, eds, Understanding Robust and Exploratory Data Analysis. 1983, John Wiley & Sons. ISBN 0-471-09777-2. Theoretical background and quantitative guidance for some of Tukey's EDA techniques, including stem-and-leaf diagrams, letter-value displays, boxplots, data transformations, resistant regression, two-way analysis, examining residuals, and robust estimation.
*** Huff, Darrell, How to Lie With Statistics. 1954, W. W. Norton & Company, New York. ISBN 0-393-31072-8 (paper). A classic. Everybody should read this. It's fun to read and takes a short evening.
* See [Madansky], below.
*** Tufte, Ed. The Visual Display of Quantitative Information. 1983, Graphics Press, CT. ISBN 0-961-39210-X. Seminal and popular work criticizing how graphics communicate information. Memorable ideas include the "lie factor," maximizing the data-ink ratio (by minimizing the ink), "chartjunk," and the "small multiple."
** Tukey, John. W. Exploratory Data Analysis. 1977, Addison-Wesley. ISBN 0-201-07616-0. Original techniques for pencil-and-paper analysis of data ("EDA"), presented clearly and simply yet penetrating deeply into the subject with many examples from real data sets.
Lloyd, Emlyn, Handbook of Applicable Mathematics, Volume II: Probability. 1980, John Wiley & Sons, New York. ISBN 0-471-27821-1. This reference defines the most basic discrete and continuous probability distributions, including the lognormal, derives their properties, and shows how to use them, combine them, and derive additional properties of them. It requires no mathematical sophistication beyond some experience with sums and integrals.
* See [Morgan and Henrion], below.
** See [Stuart and Ord], above.
* USEPA, Supplemental Guidance to RAGS: Calculating the Concentration Term. OSWER Publication 9285.7-081 May 1992 (8 pages). Details and examples of how the EPA expects upper confidence limits of the mean to be computed for Superfund risk assessments.
*** Kiefer, Jack Carl, Introduction to Statistical Inference. 1987, Springer-Verlag, New York. ISBN 0-387-96420-7. Clearly and succinctly describes the theory behind estimation, regression, and hypothesis testing. Describes, compares, and critically evaluates many statistical procedures, including Bayes, minimax, unbiased, maximum likelihood, and method of moments. Uses only (one variable) calculus and a little bit of linear algebra, but is intellectually very demanding.
* E. L. Lehmann, Theory of Point Estimation. 1991, Wadsworth, Inc. ISBN 0-534-15978-8. Advanced. Provides the theoretical foundation. For an introduction to this material see [Kiefer].
*** Hahn, Gerald J., and William Q. Meeker, Statistical Intervals. 1991, John Wiley & Sons, New York. ISBN 0-471-88769-2. If you need to compute an interval--confidence, prediction, tolerance--then you must have this book. Provides parametric and non-parametric tests in the form of formulas, graphics, and extensive tables hard to find anywhere else.
*** See [Kiefer] (Parameter estimation, above).
*** USEPA, Statistical Analysis of Ground-Water Monitoring Data at RCRA Facilities. Addendum to Interim Final Guidance. 1992. Discusses many issues raised by the 1988 guidance, including testing distributions for normality, checking for constant variance (homoscedasticity), using power curves, and strategies for multiple comparisons. Available on the Internet at http://www.epa.gov/correctiveaction/resource/guidance/sitechar/gwstats/gwstats.htm#July1992
** Thompson, Steven K, Sampling. 1992, John Wiley & Sons, New York. This is statistical sampling from the perspective of an environmental statistician. Like the classical "cookbook" text, this one provides the formulas and the worked examples. Unlike the cookbook, it also provides rigorous derivations, occasional discussions of issues, and some exercises with answers, and thereby can be read on its own as a self-contained text. It also compares the sampling procedures, sometimes presenting simulation results to establish which procedures work best in which circumstances. Includes a section on methods of "adaptive cluster sampling". The book is accessible to people with minimal statistical or mathematical skills, although reading the derivations of course requires a good background in statistical theory. If you know the difference between a parameter and an estimator you're all set.
* See [van Groenigen], below.
* Ward, Robert C., Jim C. Loftis, and Graham B. McBride, Design of Water Quality Monitoring Systems. 1990, Van Nostrand Reinhold, New York. ISBN 0-442-00156-8. Includes chapters on statistics and data analysis focusing on water monitoring data. Provides useful guidance on designing systems to monitor groundwater and surface water quality parameters. Introduces the "wheel and axle" framework. About a third of this book is case studies.
* Belsley, David A., Edwin Kuh, and Roy Welsch, Regression Diagnostics. 1980, John Wiley & Sons, NY. ISBN 0-471-05856-4. The standard reference on what can go wrong with regression, why it does, how to identify it, and how to fix it. This is a specialized book, but a few hours spent with it will improve your approach to all linear modeling problems.
** Madansky, Albert, Prescriptions for Working Statisticians. 1988, Springer-Verlag, New York. ISBN 0-387-96627-7. Details make the difference between a "textbook problem" and a "real-world" problem. Madansky focuses on the details that cause standard statistical procedures to fail. He provides diagnostic tests to identify when failure might occur and improved procedures to handle the non-textbook cases. Each section provides a worked example, a good discussion, and a theoretical derivation (something usually lacking from such books). There are occasional misprints but they are not serious. Excellent reference text.
* Currie, Lloyd A., ed., Detection in Analytical Chemistry. 1988, American Chemical Society. ISBN 0-84212-1445-X. A series of articles including a tutorial on estimating detection limits for environmental analysis, interlaboratory detection limits, and analytical calibration. Ends with panel discussions on "real-world limitations to detection" and on how to include low-level data in computer databases. The articles require some statistical sophistication.
** Chatfield, C., The Analysis of Time Series. 1989, Chapman and Hall, London and New York. ISBN 0-412-31820-2 (paper). This book aims "to provide a comprehensible introduction which considers both theory and practice," and does so very nicely. It is not too long (about 220 pages), is pitched at the undergraduate level, and contains answers to some exercises.
** Deutsch, Clayton V., and Andre G. Journel, GSLIB: Geostatistical Software Library and User's Guide. 1992, Oxford University Press, New York. ISBN 0-19-507392-4. Includes software source code on diskette. If you want to perform stochastic simulation or kriging then read the text. If you need to do anything different, creative, or specialized, then this code (written in Fortran) is the place to start.
* Ripley, Brian D., Spatial Statistics. 1981, John Wiley & Sons, NY. ISBN 0-471-08367-4.
van Groenigen, Jan-Willem, Constrained Optimisation of Spatial Sampling. 1999, CIP-Data Koninklijke Biliotheek, Den Haag. ISBN 90-6164-156-X. This Ph.D. thesis contains recent results on developing soil sampling plans that optimize criteria based on geostatistical models. Introduces "spatial simulated annealing" (SSA).
** See [Cullen and Frey], below.
*** USEPA, Risk Assessment Guidance for Superfund Volume 3 Part A: Process for Conducting Probabilistic Risk Assessment (RAGS 3A). 2000. Available in draft on the Internet at http://www.epa.gov/superfund/programs/risk/rags3adt/. Self-contained course in selecting input probability distributions, characterizing distributions, goodness-of-fit tests, and other practical issues. Provides examples of EDFs, probability plots, utilizing various distributions to model inputs to calculations. Discusses issues such as how many iterations to perform, how to perform so-called "2D" Monte Carlo Analysis, how to perform sensitivity analyses, and how to interpret output distributions.
** Cullen, Allison C., and H. Christopher Frey, Probabilistic Techniques in Exposure Assessment (A Handbook for Dealing with Variability and Uncertainty in Models and Inputs). 1999, Plenum Press, New York. ISBN 0-306-45957-4 (paper). Self contained text on probabilistic analysis in risk assessment.
* Keeney, Ralph L. and Howard Raiffa, Decisions With Multiple Objectives. 1993, Cambridge University Press, Cambridge, New York, and Melbourne. ISBN 0-521-43883-7 (paper). Rigorous theory for evaluating trade-offs among multiple objectives and preferences.
*** Morgan, M. Granger, and Max Henrion, Uncertainty. 1990, Cambridge University Press, Cambridge, New York, and Melbourne. ISBN 0-521-42744-4 (paper). Good, readable introduction to quantitative policy analysis, modeling uncertainty (including probability distributions), decision analysis, and communicating uncertainty.
*** Rodricks, Joseph V., Calculated Risks (The toxicity and human health risks of chemicals in our environment). 1992, Cambridge University Press, Cambridge, New York, and Melbourne. ISBN 0-521-42331-7 (paper). "The central purpose of this book is to describe how scientists come to understand the toxic properties of ... chemicals and the health risks they may pose." If you want to know what environmental risk assessment is about, this is a good place to begin. It does not presuppose any specialized knowledge of biology or chemistry.
*** See [USEPA], above.
* Davis, John C., Statistics and Data Analysis in Geology. 1986, John Wiley & Sons, New York. ISBN 0-471-08079-9. Includes long chapters on analyzing sequences of data, maps, and multivariate analysis. Lots of explanation and readable with minimal background (even in geology).
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This page was created 4 December 2000 and last updated 7 May 2001.