Random without replacement is not random: Caveat emptor

作者: Chris Blais

DOI: 10.3758/BRM.40.4.961

关键词: Machine learningComputer scienceStatisticsSoftwareSelection methodArtificial intelligenceCaveat emptorPsychology (miscellaneous)Experimental and Cognitive PsychologyArts and Humanities (miscellaneous)General psychologyDevelopmental and Educational Psychology

摘要: The vast majority of psychology labs rely on prepackaged software applications (e.g., E-Prime) for the programming experiments. These programs are often used stimulus selection, and many use a selection method referred to as random without replacement. We demonstrate how replacement deviates from we detail biases that result. also demonstrate, in simple experiment, these biases, if left unchecked, can influence behavior. Recommendations reducing impact performance when is discussed.

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