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The Multi-group Experiment

Panoramica

Source: Laboratories of Gary Lewandowski, Dave Strohmetz, and Natalie Ciarocco—Monmouth University

A multi-group design is an experimental design that has 3 or more conditions/groups of the same independent variable. This video demonstrates a multi-group experiment that examines how different interethnic ideologies (multiculturalism and color-blind) influence feelings about diversity and actions toward and out-group member. In providing an overview of how a researcher conducts a multi-group experiment, this video shows viewers how to distinguish levels in variables, common types of conditions/groups to use (including placebo and empty-control conditions/groups), the process of conducting the study, the collection of results, and the consideration of their implications.   

Procedura

1. Introduction of topic/research question

  1. Research question: People are unique and different, yet mostly the same. When it comes to interacting with other ethnicities, which perspective is better? We could focus on and appreciate our differences (a multicultural perspective), or focus on the many similarities we share (a color blind perspective). If one is more effective, does it have to be explicit (i.e., does the person need to realize it)? The researcher then forms a hypothesis based on educated

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Risultati

After collecting data from 88 people, perform a one-way analysis of variance (ANOVA) comparing the four conditions/groups (multicultural, colorblind, control, and empty control) to see how they influenced attitudes toward the outgroup member. As shown in Figure 1, those in the multicultural group had the most favorable attitude compared to all other conditions.

Figure 1

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Tags
Multi group ExperimentExperimental DesignIndependent VariableDependent VariableLevels conditionsControl GroupTwo group DesignMultiple group DesignEffect Of Independent VariableVariable ManipulationData AnalysisParticipant AttitudesRandom Assignment

Vai a...

0:00

Overview

1:15

Experimental Design

3:40

Running the Experiment

5:28

Representative Results

6:04

Applications

6:59

Summary

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