Experiment Design and Statistical Methods For Behavioural and Social Research
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.
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Experiment 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.
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Introduction to four basic designs
Overview of concepts and techniques
Singlefactor independent groups design
Singlefactor repeated measures design
Twofactor independent groups design
Singlefactor independent groups design with covariate
Contrasts and comparisons among means
Power and sensitivity in design decisions
Unbalanced NonRandomized and Survey Designs
Absent adjusted analysis of variance ANOVA summary table appropriate bar chart between-groups biofeed blocking factor calculation cell means Chapter coefficients comparison conditions effect confounding variable continuous covariate contrast correlation degrees of freedom dependent variable deviations diet differences digit displayed drug dyslexic error exam grade example experiment experimental F-test formula fvi fvi gerbils group means Hence independent groups design individuals Interaction diagram level of factor locus of control machine main effect mean numbers mean scores mean square measurements MSerror multiple regression number of subjects obtained oi ri overall mean p-value population posteriori professional motivation randomly allocated reject H0 represented Residual sampling fluctuation sensitivity simple effect smoker status Source df SS Source SS df speed sums of squares technique test of significance total SS two-factor design unadjusted variance estimate variation Venn diagram weight within-groups within-subjects factors WW design