Experimental Design in Behavioural Research
The Book Has Been Addressed To The Students And Researchers In The Disciplines Of Psychology, Education, Sociology, Social-Work, Medicine, Management, And Allied Disciplines. It Has Been Written For Those Who Do Not Possess Sophisticated Mathematical Background. Various Designs And Their Analyses Have Been Presented In Simple Understandable Language. The Intended Emphasis Is To Make The Reader Understand The Basic Principles Of Experimental Design, Layout For Data Collection, Analysis Of Data, Interpretation Of Results Of Experimental Outcome. It Offers An Integrated Approach Placing Due Emphasis On Theory, Application, And Computational Procedures. Schematic Representations Of Analysis For Each Design Is A Novel Feature Of This Book, It Makes The Analysis Simple And Easy To Comprehend. Each Design Includes General Layout For Data Collection, Schematic Representation Of The Analysis, Followed By Numerical Example With Detailed Solution And Interpretation. Numerous Illustrations, Many From Published Research, Are Provided With The Intent To Equip The Reader To Develop Insight Into The Intricacies Of Research Strategy. Special Treatment Has Been Given To Within Subject And Mixed Designs. Multivariate Analysis Of Variance, Analysis Of Covariance, And Also Analysis Of Variance By Ranks Have Been Included.
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BASIC TERMINOLOGY IN EXPERIMENTAL DESIGN
The Foundation of Experimental Design
Single Factor Experiments
Comparison Among Treatment Means
Two Factors p x q
Three Factors pxqxr
Latin Square Designs
CrossOver and GrecoLatin Square Designs
Higher Dimensional Designs
4x4 Latin square analysis of variance ANOVA BxSs cells sum CM CM CM component Computation correction term critical value CxSs within groups degrees of freedom design with repeated df attributable df General Form differences dividing exceeds the critical experiment with repeated experimental design F ratios factorial experiment finally the correction freedom associated groups sum Latin square design layout levels of factor main effect null hypothesis number of levels number of observations number of subjects numerical example orthogonal polynomials outcome Partitioning of Total presented in Table randomly repeated measures respect Schematic representation scores Similarly simple effects Source of Variation squares due squares is based SS and df Step subjects sum subjects within groups sum of squares summary table term is subtracted Test of Significance total number Total SS total sum Total Variation treatment combinations treatment means treatment sum Type I error variable Variation and df variation due