Analysis of Variance

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Analysis of Variance

A process of determining similarities between like groups. Analysis of variance is used in marketing to determine how likely groups with similar demographic backgrounds are to respond to a particular campaign.
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Further analyses of these cognitions were conducted by a series of Factorial ANOVAs and post hoc analyses, in the form of independent samples t-tests with adjusted p = 01 (3).
Three types of inferential analytic techniques were employed to test four (4) non-directional hypotheses: the independent sample t-test, 2 x 2 factorial ANOVA and Pearson product moment correlation tests.
Factorial ANOVA results indicated significant interaction effects for five of the seven dependent variables when severity, employment, and gender were considered, and MANOVA results indicated significant interaction for each cluster of dependent variables.
The differences in the mood scores across the independent variables were analysed using mixed factorial ANOVA.
Table 1 4 x 2 Factorial ANOVA IV: Classification and Environment DV: Intrinsic ROS Score Source SS df MS Corrected 956.
Data analysis was conducted utilizing a factorial ANOVA with repeated measures factors (Pre-test, post-test, and follow-up) for the experimental group only.
Neutral Art) Mixed Factorial ANOVA Source df F p Priming Condition 1 .
Table 3 contains results from the factorial ANOVA that examined the effects of in-school music experience and outside/private instruction on the academic and social benefit scale.
To assess stereotype rebound effects in suppressors' writing, we used a 2 (task instruction: suppress, control) x 2 (stereotype condition: poor, wealthy) mixed factorial ANOVA with repeated measures on the last factor.
First, response accuracy and reaction times on the letter-identification task were analyzed in mixed-model factorial ANOVA (evaluation instructions by location by valence), with repeated measures for valence.