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Author: Wayne W. Daniel Publisher: ISBN: Category : Mathematics Languages : en Pages : 504
Book Description
Descriptive statistics; Probability; Probability distributions; Sampling distributions; Estimating population parameters; Testing hypotheses about population parameters; Experimental design; Analysis of variance; Simple linear regression and correlation analysis; Some uses of chi-square; Nonparametric statistics.
Author: Wayne W. Daniel Publisher: ISBN: Category : Mathematics Languages : en Pages : 504
Book Description
Descriptive statistics; Probability; Probability distributions; Sampling distributions; Estimating population parameters; Testing hypotheses about population parameters; Experimental design; Analysis of variance; Simple linear regression and correlation analysis; Some uses of chi-square; Nonparametric statistics.
Author: Wayne W. Daniel Publisher: Wiley ISBN: 1119282373 Category : Medical Languages : en Pages : 720
Book Description
The ability to analyze and interpret enormous amounts of data has become a prerequisite for success in allied healthcare and the health sciences. Now in its 11th edition, Biostatistics: A Foundation for Analysis in the Health Sciences continues to offer in-depth guidance toward biostatistical concepts, techniques, and practical applications in the modern healthcare setting. Comprehensive in scope yet detailed in coverage, this text helps students understand—and appropriately use—probability distributions, sampling distributions, estimation, hypothesis testing, variance analysis, regression, correlation analysis, and other statistical tools fundamental to the science and practice of medicine. Clearly-defined pedagogical tools help students stay up-to-date on new material, and an emphasis on statistical software allows faster, more accurate calculation while putting the focus on the underlying concepts rather than the math. Students develop highly relevant skills in inferential and differential statistical techniques, equipping them with the ability to organize, summarize, and interpret large bodies of data. Suitable for both graduate and advanced undergraduate coursework, this text retains the rigor required for use as a professional reference.
Author: Deborah G. Mayo Publisher: Cambridge University Press ISBN: 1108563309 Category : Mathematics Languages : en Pages : 503
Book Description
Mounting failures of replication in social and biological sciences give a new urgency to critically appraising proposed reforms. This book pulls back the cover on disagreements between experts charged with restoring integrity to science. It denies two pervasive views of the role of probability in inference: to assign degrees of belief, and to control error rates in a long run. If statistical consumers are unaware of assumptions behind rival evidence reforms, they can't scrutinize the consequences that affect them (in personalized medicine, psychology, etc.). The book sets sail with a simple tool: if little has been done to rule out flaws in inferring a claim, then it has not passed a severe test. Many methods advocated by data experts do not stand up to severe scrutiny and are in tension with successful strategies for blocking or accounting for cherry picking and selective reporting. Through a series of excursions and exhibits, the philosophy and history of inductive inference come alive. Philosophical tools are put to work to solve problems about science and pseudoscience, induction and falsification.
Author: Wayne W. Daniel
Author: Wayne W. Daniel
Author: Wayne W. Daniel
Author: Library of Congress. Copyright Office
Author: Library of Congress. Copyright Office
Author: Wayne W. Daniel
Author: Library of Congress. Copyright Office
Author: 
Author: Library of Congress. Copyright Office
Author: 
Author: Deborah G. Mayo