Abstract and Keywords
Sound and defensible decisions regarding the practice of education and psychology cannot be made without reliable and valid data. Data collection to inform decisions must be carefully planned within the framework of a rigorous research study designed to answer well-articulated research questions. Once collected, the data must be analyzed and summarized using appropriate procedures. The classical statistical framework for drawing inferences and making decisions, null hypothesis significance testing, has been severely criticized by prominent researchers in the field. The purposes of this chapter are to provide school psychologists with a clear description of how the statistical reasoning process is correctly applied to enable valid statistical inference leading to sound decisions; to describe the notion of effect size and power and provide tools for computing these; to describe procedures for testing hypotheses that incorporate tolerance limits on what differences between parameters are meaningful; and to provide an introduction to the Bayesian framework that permits probabilistic statements about parameters and hypotheses.
Keywords: Keywords, Null hypothesis significance testing, school psychology, effect size, noncentral distributions, power, equivalence testing, range null hypothesis, cluster randomized design, Bayesian analysis, decision theory
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