analysis of variance

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analysis of variance

n.
A method for assessing the contribution of an independent variable or controllable factor to the observed variation in an experimentally observed dependent variable.

analysis of variance

n
(Statistics) statistics any of a number of techniques for resolving the observed variance between sets of data into components, esp to determine whether the difference between two samples is explicable as random sampling variation with the same underlying population. Abbreviation: ANOVA
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Noun1.analysis of variance - a statistical method for making simultaneous comparisons between two or more meansanalysis of variance - a statistical method for making simultaneous comparisons between two or more means; a statistical method that yields values that can be tested to determine whether a significant relation exists between variables
statistics - a branch of applied mathematics concerned with the collection and interpretation of quantitative data and the use of probability theory to estimate population parameters
multivariate analysis - a generic term for any statistical technique used to analyze data from more than one variable
References in periodicals archive ?
Level of Significance for the variations of means was tested using four factorial ANOVA. Duncan's multiple range test (DMRT) at (p was used to compare the variance between means of the treatments (Steel et al., 1997).
A Factorial ANOVA was used in the analysis to verify if the accuracy in the judgment of the images varied according to the previous experience of the judges and the sound class.
To analyze differences associated with the main and interaction effects of group characteristics, a factorial ANOVA was performed using CENVE scores as dependent variables and age, gender, and educational level as fixed factors.
To evaluate the difference in the amount of surround inhibition after rPAS between focal dystonia and controls, we performed a factorial ANOVA. Moreover, to evaluate differences in SEP amplitude between dystonic patients and controls, we used the unpaired Mann Whitney U test.
Comparisons were performed, first, through one-way ANOVA including controls and treatments, then, by using a two-way factorial ANOVA with interactions including only the treatments with subsequent post hoc tests (Duncan).
This study used a factorial analysis of variance (factorial ANOVA) that consisted of two independent variables and one or more dependent variable (Mertler & Vannatta, 2010).
Analysis of results (Figure 1) by factorial ANOVA revealed that the elastic sleeve tested in this study reduced the anterior displacement of the tibia by a small (max.
A 3 (Participant group: college students, university students and business persons) x 2 (Expectancy: positive or negative) Factorial ANOVA of mixed design was conducted (sphericity not assumed, Greenhouse-Geisser correction implemented).
Additionally, a series of 2 x 2 factorial ANOVA were performed to test main and interaction effects of gender and level of study on various dimensions of the information seeking anxiety construct (hypotheses three).
Apoptosis was monitored by (a) western blot analysis for cleaved caspase-3 ([beta]-actin was used as loading control), (b) TUNEL staining (n = 3 independent experiments with 2 counting regions of 200 cells/region in duplicate; ### P < 0.001 and # P < 0.05 versus 0 [micro]g/mL; *** P < 0.001 versus [Casp3.sup.+/+]; factorial ANOVA with genotype and treatment as category factors; Dunnett post hoc) and (c) caspase-3/7 fluorometric activity assay (n = 3 independent experiments; ## P < 0.01, # P < 0.05, and NS, not significant, versus 0 [micro]g/mL; *** p < 0.001 versus [Casp3.sup.-/-]; factorial ANOVA with genotype and treatment as category factors; Dunnett post hoc).
Immediate data collection was not possible due to the time taken to row back to the boating dock area Data Analysis Hypotheses 1 and 2 were addressed across the three training conditions using a 3 (condition; low moderate high) x 2 (gender) mixed factorial ANOVA. Differences in attentional strategy across the two competition distances were analyzed using a 2 (race diatance) x 2 (gender) mixed factorial ANOVA.
The data on the tube numbers and length were analyzed with a 3-way factorial ANOVA using days, quadrat, and species as variables [25, 26].