Does the Left Hair Part Look Better (or Worse) Than the Right?

In the present research, consisting of 2 correlational studies (N = 616) including a representative U.S. sample and 2 experiments (N = 350), the authors investigated how stereotypes and emotions shape behavioral tendencies toward groups, offering convergent support for the behaviors from intergroup affect and stereotypes (BIAS) map framework. Warmth stereotypes determine active behavioral tendencies, attenuating active harm (harassing) and eliciting active facilitation (helping). Competence stereotypes determine passive behavioral tendencies, attenuating passive harm (neglecting) and eliciting passive facilitation (associating). Admired groups (warm, competent) elicit both facilitation tendencies; hated groups (cold, incompetent) elicit both harm tendencies. Envied groups (competent, cold) elicit passive facilitation but active harm; pitied groups (warm, incompetent) elicit active facilitation but passive harm. Emotions predict behavioral tendencies more strongly than stereotypes do and usually mediate stereotype-to-behavioral-tendency links.

On the basis of previous research, the authors hypothesize that (a) person descriptive terms can be organized into the broad dimensions of agency and communion of which communion is the primary one; (b) the main distinction between these dimensions pertains to their profitability for the self (agency) vs. for other persons (communion); hence, agency is more desirable and important in the self-perspective, and communion is more desirable and important in the other-perspective; (c) self-other outcome dependency increases importance of another person's agency. Study 1 showed that a large number of trait names can be reduced to these broad dimensions, that communion comprises more item variance, and that agency is predicted by self-profitability and communion by other-profitability. Studies 2 and 3 showed that agency is more relevant and desired for self, and communion is more relevant and desired for others. Study 4 showed that agency is more important in a close friend than an unrelated peer, and this difference is completely mediated by the perceived outcome dependency. (c) 2007 APA, all rights reserved.

Null-hypothesis significance testing remains the standard inferential tool in cognitive science despite its serious disadvantages. Primary among these is the fact that the resulting probability value does not tell the researcher what he or she usually wants to know: How probable is a hypothesis, given the obtained data? Inspired by developments presented by Wagenmakers (Psychonomic Bulletin & Review, 14, 779-804, 2007), I provide a tutorial on a Bayesian model selection approach that requires only a simple transformation of sum-of-squares values generated by the standard analysis of variance. This approach generates a graded level of evidence regarding which model (e.g., effect absent [null hypothesis] vs. effect present [alternative hypothesis]) is more strongly supported by the data. This method also obviates admonitions never to speak of accepting the null hypothesis. An Excel worksheet for computing the Bayesian analysis is provided as supplemental material.