Experiment Design And Statistical Methods For Behavioural And Social Research


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Experiment Design and Statistical Methods For Behavioural and Social Research


Experiment Design and Statistical Methods For Behavioural and Social Research

Author: David R. Boniface

language: en

Publisher:

Release Date: 2017


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"Experiment Design and Statistical Methods introduces the concepts, principles, and techniques for carrying out a practical research project either in real world settings or laboratories - relevant to studies in psychology, education, life sciences, social sciences, medicine, and occupational and management research.The text covers:repeated measuresunbalanced and non-randomized experiments and surveyschoice of designadjustment for confounding variablesmodel building and partition of variancecovariancemultiple regressionExperiment Design and Statistical Methods contains a unique extension of the Venn diagram for understanding non-orthogonal design, and it includes exercises for developing the reader's confidence and competence. The book also examines advanced techniques for users of computer packages or data analysis, such as Minitab, SPSS, SAS, SuperANOVA, Statistica, BMPD, SYSTAT, Genstat, and GLIM."--Provided by publisher.

Research Design & Statistical Analysis


Research Design & Statistical Analysis

Author: Arnold D. Well

language: en

Publisher: Psychology Press

Release Date: 2003-01-30


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"Free CD contains several real and artificial data sets used in the book in SPSS, SYSTAT, and ASCII formats"--Cover

Statistical Power Analysis for the Behavioral Sciences


Statistical Power Analysis for the Behavioral Sciences

Author: Jacob Cohen

language: en

Publisher: Routledge

Release Date: 2013-05-13


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Statistical Power Analysis is a nontechnical guide to power analysis in research planning that provides users of applied statistics with the tools they need for more effective analysis. The Second Edition includes: * a chapter covering power analysis in set correlation and multivariate methods; * a chapter considering effect size, psychometric reliability, and the efficacy of "qualifying" dependent variables and; * expanded power and sample size tables for multiple regression/correlation.