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Experimental Design

James B. Weaver, III


Experimental design provides the logical architecture for scientific research examining causal relationships. Most people intuitively recognize causal relationships. It is not uncommon to hear, for instance, that increased time studying caused an improved test grade, that a “sweet tooth” enabled a friend's weight gain, or that traffic congestion instigated a “road rage” incident. The tendency to attribute causality, often spontaneously, in commonsense explanations of everyday behaviors punctuates both private and public discourse and appears a distinctively human characteristic ( Frey et al. 2000 ). In scientific endeavors, we are typically much more deliberate when making causality inferences ( Hill 1965 ) and often rely on experimentation to inform judgments about causal relationships. Experimentation is a process used to determine the extent, if any, of causal connections between two or more variables. Through experimentation, we test predictions about causal relationships by manipulating aspects of a particular context or activity and then observing the resulting perceptual and behavioral outcomes. Effective experimentation is guided by a testable descriptive causal →  hypothesis asserting the conditions under which a manipulable independent variable, commonly called an “experimental treatment” or “intervention,” involving at least two levels, influences measurable outcomes ... log in or subscribe to read full text

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