F test

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F test

[′ef ‚test]
(statistics)
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One-way analysis of variance (ANOVA) or F-test is one of the most common statistical techniques in educational and psychological research (Keselman et al.
Testing of these hypotheses is based on two sets of asymptotic critical values of F-test given in the [8].
Significant predictors were first identified on a univariate basis using the parametric t-test or F-test, and the multivariate non-parametric Boosted Trees method was also applied for the sake of comparison.
An F-test rejects equality of mean scores and a Bonferroni multiple-comparison test isolates significant differences between: Australian (2.
An independent samples f-test was calculated at a confidence interval of 95% in SPSS version 21 using the data collected with the OC questionnaire.
23 orthogonal contrast F-test Contrast 1 ns ns ns ns ns ns ns Contrast 2 ns ns ns * ns ns * Contrast 3 ns ns ns ns ns * * (1) SM + SO--control diet with soybean meal and oil; MC+SO--control diet with 25% canola meal replacing soybean meal; MC + CO--control diet with 25% canola meal replacing soybean meal and canola oil completely replacing soybean oil; SM+OC - control diet with soybean meal and canola oil.
First, we see that the F-test is statistically significant, which means that the model is statistically significant.
The data were analyzed using a repeated measured ANOVA model, and comparison between stages was performed using the paired f-test by SPSS software version 16.
The result of F-test shown there are influenced together between variable with F-test = 9,555 and sig.
The F-test criterion is high for all 13 models, with very low p-values (less than 0.
The paired f-test provides an understanding of the difference between the scores observed at the beginning of the class and those observed after completion of the class.