analysis of variance

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Synonyms for analysis of variance

a statistical method for making simultaneous comparisons between two or more means

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The Factorial ANOVA (2 factors) was used in the analysis, considering the experience of the judges (experienced vs.
Table 3 summarizes the results of factorial ANOVA 2 (gender) x 3 (age group) x 3 (educational level).
Factorial ANOVA did not show any significant difference between the amount of ratio MU/(M + U) * 100 after the 5 Hz rPAS between dystonic patients and controls in the APB muscle.
A 4 (Positive expectancy: social, fun, sex, tension reduction) x 3 (Participant group: college student, university student or business person) Factorial ANOVA of mixed design was conducted (sphericity not assumed, Greenhouse-Geisser correction implemented).
The results of running a series of 2 x2 factorial ANOVA tests revealed a statistically significant main effect for gender on "barriers associated with information resources" dimension of the information seeking anxiety.
Necrosis was monitored by (a) morphological analysis (necrotic cells were characterized by cellular oncosis (black arrows) while apoptotic cells showed cellular shrinkage (black arrowheads) and membrane blebbing (open arrowhead)) (scale bar: 25 [micro]m (BMDM) and 50 [micro]m (VSMCs)) and (b) PI labeling (n = 3 independent experiments with 2 counting regions of 150 cells/region in duplicate; ### P < 0.001 versus0 [micro]g/mL; *** P < 0.001 versus [Casp3.sup.+/+]; factorial ANOVA with genotype and treatment as category factors; Dunnett post hoc).
Results of a 3 x 2 mixed factorial ANOVA revealed a significant main effect for training intensity F(2 592) = 936.07 p less than .001 yp revealed significant differences between the three training conditions and a positive relationship between training intensity and association (see Table 1); therefore Hypothesis 1 was accepted.
TABLE 1: The results of 3-way factorial ANOVA on the effects of non-predators on the tube numbers per quadrat (10 * 10.7 [cm.sup.2]) when the non-predators were present as separately as individual species.
A follow-up two-way factorial ANOVA was then performed on each dependent variable individually.
A 3-factor (month, sleeves, and Tanglefoot) factorial ANOVA showed that month of exposure had no significant effect on survival to fifth instar (F = 0.17; df = 3; P = 0.92) or survival to pupa (F = 0.05; df = 3; P = 0.83).
One factorial ANOVA revealed a significant difference among the frequency of food items.
In line with the graphical interpretation, a factorial ANOVA confirms that the effects of the performance of Person A (F(4,228)=118.06; p<.001) and Person B (F(4,228)=107.39; p<.001) as well as their interaction (F(16,912)=10.02; p<.001) are significantly different from zero.
Topics discussed include data coding and exploratory analysis, reliability measurements, exploratory factor analysis, interpreting inferential statistics, multiple regression, discriminate analysis, factorial ANOVA, and multivariate analysis of variance.
We performed data analysis using Factorial ANOVA. The analysis is guided by the Research Framework (Figure 1) that shows the relationship between the dependent (LE or Leadership Effectiveness) and two independent variables (LC or Leadership Competencies and gender).