Bayesian Statistics for Beginners: a step-by-step approach

Bayesian statistics is currently undergoing something of a renaissance. At its heart is a method of statistical inference in which Bayes' theorem is used to update the probability for a hypothesis as more evidence or information becomes available. It is an approach that is ideally suited to making initial assessments based on incomplete or imperfect information; as that information is gathered and disseminated, the Bayesian approach corrects or replaces the assumptions and alters its decision-making accordingly to generate a new set of probabilities. As new data/evidence becomes available the probability for a particular hypothesis can therefore be steadily refined and revised. It is very well-suited to the scientific method in general and is widely used across the social, biological, medical, and physical sciences. Key to this book's novel and informal perspective is its unique pedagogy, a question and answer approach that utilizes accessible language, humor, plentiful illustrations, and frequent reference to on-line resources. Bayesian Statistics for Beginners is an introductory textbook suitable for senior undergraduate and graduate students, professional researchers, and practitioners seeking to improve their understanding of the Bayesian statistical techniques they routinely use for data analysis in the life and medical sciences, psychology, public health, business, and other fields.

Science & Math

Mickey, Ruth M.

Donovan, Therese M.

Mathematics

Oxford University Press

Bayesian statistics is currently undergoing something of a renaissance. At its heart is a method of statistical inference in which Bayes' theorem is used to update the probability for a hypothesis as more evidence or information becomes available. It is an approach that is ideally suited to making initial assessments based on incomplete or imperfect information; as that information is gathered and disseminated, the Bayesian approach corrects or replaces the assumptions and alters its decision-making accordingly to generate a new set of probabilities. As new data/evidence becomes available the probability for a particular hypothesis can therefore be steadily refined and revised. It is very well-suited to the scientific method in general and is widely used across the social, biological, medical, and physical sciences. Key to this book's novel and informal perspective is its unique pedagogy, a question and answer approach that utilizes accessible language, humor, plentiful illustrations, and frequent reference to on-line resources. Bayesian Statistics for Beginners is an introductory textbook suitable for senior undergraduate and graduate students, professional researchers, and practitioners seeking to improve their understanding of the Bayesian statistical techniques they routinely use for data analysis in the life and medical sciences, psychology, public health, business, and other fields.

This set contains: 9780471469438 Regression and ANOVA: An Integrated Approach Using SAS(R) Software by Keith E. Muller, Bethel A. Fetterman and 9780471370383 Applied Statistics: Analysis of Variance and Regression, Third Edition by Ruth M. Mickey, Olive Jean Dunn, Virginia A. Clark.

Regression and ANOVA: An Integrated Approach Using SAS Software + Applied Statistics: Analysis of Variance and Regression, Third Edition Set

Dunn, Olive Jean

Clark, Virginia A.

Muller, Keith E.

Fetterman, Bethel A.

Wiley-Interscience

Applied Statistics: Analysis of Variance and Regression

This work has been thoughtfully designed so that it serves equally well as a reference for the practitioner and as a self-contained textbook for the advanced student. * Rewritten to maintain clarity and brevity while expanding the coverage of previous editions. * Changes to design-related topics include increased discussion of mixed models and random effects, greater emphasis on regression and data screening, and more use of graphs throughout. * Includes both graded and challenging exercises. * Liberal computer discussions now supplemented with SAS and SPSS.

Biological Sciences

wiley

Regression Analysis by Example Samprit Chatterjee and Bertram Price Bridges the gap between theory and practice of regression analysis, providing a balance between theoretical results and the analyst’s subjective judgment. Describes methods by using realistic examples that emphasize the analysis of data and that contain irregularities similar to those encountered in practice. Demonstrates how to apply theoretical results by utilizing standard—and some not so standard—summary statistics on the basis of their intuitive appeal. 1977 Interactive Data Analysis A Practical Primer Donald R. McNeil Introduces the use of Exploratory Data Analysis in scientific work. Gives a set of numerical and graphical methods to find structure in data. Illustrations show the power and simplicity of the methods, and all listings are given in Fortran and APL for all the programs used to produce displays and analysis in the text. Assumes no formal knowledge of probability, mathematics, or computing. 1977 Statistical Survey Techniques Raymond J. Jessen A comprehensive, balanced treatment of the techniques for designing surveys and analyzing their data. Describes the methods which seem to be basic to such diverse fields as public opinion measurement, sociology, political science, economics, business, various governmental agencies, biology (e.g. wildlife and fisheries), engineering (e.g. traffic studies), urban planning and management, ecological studies, and many others. 1977

Basic Statistics: A Primer for the Biomedical Sciences, 2nd Edition

See the best price to sell, buy, or rent books by Mickey, Ruth M.. BookScouter helps to compare book prices from 25+ online bookstores and 30+ buyback vendors with a single search.

Books by Mickey, Ruth M.

See the best price to sell, buy, or rent books by Mickey, Ruth M.. BookScouter helps to compare book prices from 25+ online bookstores and 30+ buyback vendors with a single search.

Bayesian Statistics for Beginners: a step-by-step approach

Bayesian Statistics for Beginners: a step-by-step approach

Regression and ANOVA: An Integrated Approach Using SAS Software + Applied Statistics: Analysis of Variance and Regression, Third Edition Set

Applied Statistics: Analysis of Variance and Regression

Basic Statistics: A Primer for the Biomedical Sciences, 2nd Edition

Applied Statistics: Analysis of Variance and Regression