Analysis of Variance and Covariance
Analysis of variance (ANOVA) and analysis of covariance (ANACOVA) are statistical techniques most suited for the analysis of data collected using experimental methods. As a result, they have been used more frequently in the fields of psychology and medicine and less frequently in sociological studies where survey methods predominate. These techniques can be, and have been, used on survey data, but usually they are performed within the analysis framework of linear regression or the "general linear model." Given their applicability to experimental data, the easiest way to convey the logic and value of these techniques is to first review the basics of experimental design and the analysis of experimental data. Basic concepts and procedures will then be described, summary measures and assumptions reviewed, and the applicability of these techniques for sociological analysis discussed.
Experimental Design and Analysis
In a classical experimental design, research subjects are randomly assigned in equal numbers to two or more discrete groups. Each of these groups is then given a different treatment or stimulus and observed to determine whether or not the different treatments or stimuli had predicted effects on some outcome variable. In most cases this outcome variable has continuous values rather than discrete categories.
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