A Logistic Regression Equation For Estimating The Probability Of A Stream Flowing Perennially In Massachusetts
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A Logistic Regression Equation for Estimating the Probability of a Stream Flowing Perennially in Massachusetts by Gardner C. Bent,Stacey Anne Archfield Pdf
... Produced to assist agencies administering the Commonwealth of Massachusetts' River Protection Act of 1996; data was collected on the characteristics of verified perennial or intermittent streams to create an equation that could be used to indicate the probability of a stream flowing perenially; available online at: www.water.usgs.gov/pubs/of/ofr02183 ...
Aldo V. Vecchia,Christopher Peter Konrad,Gardner C. Bent,John R. Mullaney,Rodney Allen Sheets,Derek B. Booth,Stacey Anne Archfield
Author : Aldo V. Vecchia,Christopher Peter Konrad,Gardner C. Bent,John R. Mullaney,Rodney Allen Sheets,Derek B. Booth,Stacey Anne Archfield Publisher : Unknown Page : 372 pages File Size : 54,9 Mb Release : 2002 Category : Abandoned mines ISBN : OSU:32435071610059
Water-resources Investigations Report by Aldo V. Vecchia,Christopher Peter Konrad,Gardner C. Bent,John R. Mullaney,Rodney Allen Sheets,Derek B. Booth,Stacey Anne Archfield Pdf
Introduction to Statistics Through Resampling Methods and R by Phillip I. Good Pdf
A highly accessible alternative approach to basic statistics Praise for the First Edition: "Certainly one of the most impressive little paperback 200-page introductory statistics books that I will ever see . . . it would make a good nightstand book for every statistician."—Technometrics Written in a highly accessible style, Introduction to Statistics through Resampling Methods and R, Second Edition guides students in the understanding of descriptive statistics, estimation, hypothesis testing, and model building. The book emphasizes the discovery method, enabling readers to ascertain solutions on their own rather than simply copy answers or apply a formula by rote. The Second Edition utilizes the R programming language to simplify tedious computations, illustrate new concepts, and assist readers in completing exercises. The text facilitates quick learning through the use of: More than 250 exercises—with selected "hints"—scattered throughout to stimulate readers' thinking and to actively engage them in applying their newfound skills An increased focus on why a method is introduced Multiple explanations of basic concepts Real-life applications in a variety of disciplines Dozens of thought-provoking, problem-solving questions in the final chapter to assist readers in applying statistics to real-life applications Introduction to Statistics through Resampling Methods and R, Second Edition is an excellent resource for students and practitioners in the fields of agriculture, astrophysics, bacteriology, biology, botany, business, climatology, clinical trials, economics, education, epidemiology, genetics, geology, growth processes, hospital administration, law, manufacturing, marketing, medicine, mycology, physics, political science, psychology, social welfare, sports, and toxicology who want to master and learn to apply statistical methods.
Common Errors in Statistics (and How to Avoid Them) by Phillip I. Good,James W. Hardin Pdf
Praise for the Second Edition "All statistics students and teachers will find in this book a friendly and intelligentguide to . . . applied statistics in practice." —Journal of Applied Statistics ". . . a very engaging and valuable book for all who use statistics in any setting." —CHOICE ". . . a concise guide to the basics of statistics, replete with examples . . . a valuablereference for more advanced statisticians as well." —MAA Reviews Now in its Third Edition, the highly readable Common Errors in Statistics (and How to Avoid Them) continues to serve as a thorough and straightforward discussion of basic statistical methods, presentations, approaches, and modeling techniques. Further enriched with new examples and counterexamples from the latest research as well as added coverage of relevant topics, this new edition of the benchmark book addresses popular mistakes often made in data collection and provides an indispensable guide to accurate statistical analysis and reporting. The authors' emphasis on careful practice, combined with a focus on the development of solutions, reveals the true value of statistics when applied correctly in any area of research. The Third Edition has been considerably expanded and revised to include: A new chapter on data quality assessment A new chapter on correlated data An expanded chapter on data analysis covering categorical and ordinal data, continuous measurements, and time-to-event data, including sections on factorial and crossover designs Revamped exercises with a stronger emphasis on solutions An extended chapter on report preparation New sections on factor analysis as well as Poisson and negative binomial regression Providing valuable, up-to-date information in the same user-friendly format as its predecessor, Common Errors in Statistics (and How to Avoid Them), Third Edition is an excellent book for students and professionals in industry, government, medicine, and the social sciences.
Common Errors in Statistics by Phillip I. Good,James W. Hardin Pdf
A guide to choosing and using the right techniques High-speed computers and prepackaged statistical routines would seem to take much of the guesswork out of statistical analysis and lend its applications readily accessible to all. Yet, as Phillip Good and James Hardin persuasively argue, statistical software no more makes one a statistician than a scalpel makes one a surgeon. Choosing the proper technique and understanding the analytical context is of paramount importance to the proper application of statistics. The highly readable Common Errors in Statistics (and How to Avoid Them) provides both newly minted academics and professionals who use statistics in their work with a handy field guide to statistical problems and solutions. Good and Hardin begin their handbook by establishing a mathematically rigorous but readily accessible foundation for statistical procedures. They focus on debunking popular myths, analyzing common mistakes, and instructing readers on how to choose the appropriate statistical technique to address their specific task. A handy checklist is provided to summarize the necessary steps. Topics covered include: * Creating a research plan * Formulating a hypothesis * Specifying sample size * Checking assumptions * Interpreting p-values and confidence intervals * Building a model * Data mining * Bayes' Theorem, the bootstrap, and many others Common Errors in Statistics (and How to Avoid Them) also contains reprints of classic articles from statistical literature to re-examine such bedrock subjects as linear regression, the analysis of variance, maximum likelihood, meta-analysis, and the bootstrap. With a final emphasis on finding solutions and on the great value of statistics when applied in the proper context, this book will prove eminently useful to students and professionals in the fields of research, industry, medicine, and government.
Regression Equations for Estimating Flood Flows for the 2-, 10-, 25-, 50-, 100-, and 500-year Recurrence Intervals in Connecticut by Elizabeth A. Ahearn Pdf
Methods for Estimating Magnitude and Frequency of Floods in the Southwestern United States by Blakemore E. Thomas,H. W. Hjalmarson,Scott D. Waltemeyer Pdf
Methods of Computation of Low Streamflow by T. A. McMahon,A. Diaz Arenas Pdf
Factors affecting low streamflow; Assessment of data used in low flow analysis; Computational procedures with adequate hydrometric data; Determination of low flow inadequate hydrometric data; Low flow forecasts.