Death Penalty Is Unfair

Statistical Tests of Mean (Ave.) Differences Among Execution Actors

When compared to the three groups that favor executions, Abolitionists reported much higher agreement scores (mean=3.77) on the index measuring the belief system that the death penalty is applied unfairly to the innocent, persons of color, and the poor. The differences in means are statistically significant. The strength of the influence of this belief system on intended actions toward executions is greater than medium. Eta Squared for this test is .13, which is greater than Eta Squared=.09, which is the standard for medium effect size.

For the three groups that support executions, all averages were in the high 'disagree' range, where 3.0 is neutral. The average for Soft Abstract Supporters is 2.99. For Hard Abstract Supporters, the average is 2.98. Among Executioners, the average is 2.87. When differences in means were tested for all three pro-execution groups, the difference was not significant. The effect size for this test is a trivial .002, due only to the slightly lower average among Executioners. When Soft Abstract Supporters and Hard Abstract Supporters were tested separately, the effect size disappeared. Eta squared is .000.



*Every person in the study had an average "score" for this belief system. That score ranged from 1.00 (strongly disagree) to 5.0 (strongly agree), where 3.0 is neither agree/disagree. Analysis of Variance (ANOVA) tests differences in average scores across groups. Inherently, ANOVA is a more powerful statistic than the Chi-Square. As with the Chi-Square, a Sig. less than .05 indicates that differences in averages are significant. Further, ANOVA provides an estimate of effect size (eta squared). With non-probability samples, effect size is a more meaningful measure of the influence of underlying belief systems on roles (intended actions) that people play as execution actors.