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Lawrence L. Kupper | Akateeminen Kirjakauppa

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Exercises and Solutions in Statistical Theory
Lawrence L. Kupper; Brian. H Neelon; Sean M. O'Brien
Taylor & Francis Inc (2013)
Pehmeäkantinen kirja
85,40
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Exercises and Solutions in Statistical Theory
Lawrence L. Kupper; Brian. H Neelon; Sean M. O'Brien
Taylor & Francis Ltd (2017)
Kovakantinen kirja
219,60
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Epidemiologic Research - Principles and Quantitative Methods
David G. Kleinbaum; Lawrence L. Kupper; Hal Morgenstern
John Wiley & Sons Inc (1982)
Kovakantinen kirja
182,60
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Student Solutions Manual for Kleinbaum's Applied Regression Analysis and Other Multivariable Methods, 5th
David G. Kleinbaum; Lawrence L. Kupper; Azhar Nizam
Cengage Learning (2013)
Pehmeäkantinen kirja
129,20
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Student Solutions Manual for Kleinbaum/Kupper/Muller S Applied Regression Analysis and Multivariable Methods, 4th
David G Kleinbaum; Kupper, Lawrence L (University of North Carolina, Chapel Hill, USA); Azhar Nizam; Muller, Keith E, PH.D. (U
Cengage Learning, Inc (2007)
Pehmeäkantinen kirja
100,30
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Exercises and Solutions in Statistical Theory
85,40 €
Taylor & Francis Inc
Sivumäärä: 388 sivua
Asu: Pehmeäkantinen kirja
Painos: 1
Julkaisuvuosi: 2013, 24.06.2013 (lisätietoa)
Kieli: Englanti
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.

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