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Quantitative methods in social research --- Mathematical statistics --- Statistical power analysis --- -Statistical power analysis --- Power analysis (Statistics) --- Selectie. Steekproeven omvang --(sociaal onderzoek) --- Statistical power analysis. --- 303.5 Selectie. Steekproeven omvang --(sociaal onderzoek) --- Research --- Statistical methods. --- #SBIB:303H510 --- 303.5 --- Statistical hypothesis testing --- Statistical methods --- Methoden sociale wetenschappen: statistische technieken, algemeen --- research --- Recherche --- Méthodes statistiques --- Research - Statistical methods

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This book presents a simple and general method for conducting statistical power analysis based on the widely used 'F' statistic. The book illustrates how these analyses work and how they can be applied to problems of studying design, to evaluate others' research, and to choose the appropriate criterion for defining "statistically significant" outcomes. 'Statistical Power Analysis' examines the four major applications of power analysis, concentrating on how to determine: *the sample size needed to achieve desired levels of power; *the level of power that is needed in a study; *the size of effect that can be reliably detected by a study; and *sensible criteria for statistical significance. Highlights of the second edition include: a CD with an easy-to-use statistical power analysis program; a new chapter on power analysis in multi-factor ANOVA, including repeated-measures designs; and a new One-Stop PV Table to serve as a quick reference guide. The book discusses the application of power analysis to both traditional null hypothesis tests and to minimum-effect testing. It demonstrates how the same basic model applies to both types of testing and explains how some relatively simple procedures allow researchers to ask a series of important questions about their research. Drawing from the behavioral and social sciences, the authors present the material in a nontechnical way so that readers with little expertise in statistical analysis can quickly obtain the values needed to carry out the power analysis. Ideal for students and researchers of statistical and research methodology in the social, behavioral, and health sciences who want to know how to apply methods of power analysis to their research.

#PBIB:2003.3 --- #SBIB:303H520 --- Methoden sociale wetenschappen: techniek van de analyse, algemeen --- Statistical hypothesis testing. --- Statistical power analysis. --- Methoden en technieken --- statistiek --- statistiek. --- Statistical hypothesis testing --- Statistical power analysis --- Power analysis (Statistics) --- Hypothesis testing (Statistics) --- Significance testing (Statistics) --- Statistical significance testing --- Testing statistical hypotheses --- Distribution (Probability theory) --- Hypothesis --- Mathematical statistics

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Why psychology is in peril as a scientific discipline - and how to save it. Psychological science has made extraordinary discoveries about the human mind, but can we trust everything its practitioners are telling us? In recent years, it has become increasingly apparent that a lot of research in psychology is based on weak evidence, questionable practices, and sometimes even fraud. The Seven Deadly Sins of Psychology diagnoses the ills besetting the discipline today and proposes sensible, practical solutions to ensure that it remains a legitimate and reliable science in the years ahead. In this unflinchingly candid manifesto, Chris Chambers draws on his own experiences as a working scientist to reveal a dark side to psychology that few of us ever see. Using the seven deadly sins as a metaphor, he shows how practitioners are vulnerable to powerful biases that undercut the scientific method, how they routinely torture data until it produces outcomes that can be published in prestigious journals, and how studies are much less reliable than advertised. He reveals how a culture of secrecy denies the public and other researchers access to the results of psychology experiments, how fraudulent academics can operate with impunity, and how an obsession with bean counting creates perverse incentives for academics. Left unchecked, these problems threaten the very future of psychology as a science - but help is here. Outlining a core set of best practices that can be applied across the sciences, Chambers demonstrates how all these sins can be corrected by embracing open science, an emerging philosophy that seeks to make research and its outcomes as transparent as possible.

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