David G. Kleinbaum

Lawrence L. Kupper

Hal Morgenstern

Epidemiologic Research Principles and Quantitative Methods DavidG. Kleinbaum, Ph.D. Lawrence L. Kupper. Ph.D. Hal Morgenstern,Ph.D. Epidemiologic Research covers the principles and methodsof planning, analysis and interpretation of epidemiologic researchstudies. It supplies the applied researcher with the mostup-to-date methodological thought and practice. Specifically, thebook focuses on quantitative (including statistical) issues arisingfrom epidemiologic investigations, as well as on the questions ofstudy design, measurement and validity. EpidemiologicResearch emphasizes practical techniques, procedures andstrategies. It presents them through a unified approach whichfollows the chronology of issues that arise during theinvestigation of an epidemic. The book's viewpoint ismultidisciplinary and equally useful to the epidemiologicresearcher and to the biostatistician. Theory is supplemented bynumerous examples, exercises and applications. Full solutions aregiven to all exercises in a separate solutions manual. Importantfeatures * Thorough discussion of the methodology of epidemiologicresearch * Stress on validity and hence on reliability * Balanced approach, presenting the most important prevailingviewpoints * Three chapters with applications of mathematical modeling

Principles and Quantitative Methods

Epidemiologic Research

Azhar Nizam

Eli S. Rosenberg

This bestseller will help you learn regression-analysis methods that you can apply to real-life problems. It highlights the role of the computer in contemporary statistics with numerous printouts and exercises that you can solve using the computer. The authors continue to emphasize model development, the intuitive logic and assumptions that underlie the techniques covered, the purposes, advantages, and disadvantages of the techniques, and valid interpretations of those techniques. Available with InfoTrac Student Collections http://gocengage.com/infotrac. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.

Applied Regression Analysis and Other Multivariable Methods

Brian. H Neelon

Sean M. O'Brien

Exercises and Solutions in Statistical Theory helps students and scientists obtain an in-depth understanding of statistical theory by working on and reviewing solutions to interesting and challenging exercises of practical importance. Unlike similar books, this text incorporates many exercises that apply to real-world settings and provides much more thorough solutions. The exercises and selected detailed solutions cover from basic probability theory through to the theory of statistical inference. Many of the exercises deal with important, real-life scenarios in areas such as medicine, epidemiology, actuarial science, social science, engineering, physics, chemistry, biology, environmental health, and sports. Several exercises illustrate the utility of study design strategies, sampling from finite populations, maximum likelihood, asymptotic theory, latent class analysis, conditional inference, regression analysis, generalized linear models, Bayesian analysis, and other statistical topics. The book also contains references to published books and articles that offer more information about the statistical concepts. Designed as a supplement for advanced undergraduate and graduate courses, this text is a valuable source of classroom examples, homework problems, and examination questions. It is also useful for scientists interested in enhancing or refreshing their theoretical statistical skills. The book improves readers’ comprehension of the principles of statistical theory and helps them see how the principles can be used in practice. By mastering the theoretical statistical strategies necessary to solve the exercises, readers will be prepared to successfully study even higher-level statistical theory.

Exercises and Solutions in Statistical Theory

P. M. Sullivan

D. Harry Chambers

Chlorine Dissolution of Several Ferroalloys

Lawrence L. Kupper

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