Bonferroni t-test

Bon·fer·ro·ni t-test

(bōn-fer-rō'nē test)
Statistical technique using Bonferroni inequality to isolate differences between comparisons; describes error rate for all comparisons taken as a group.
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Statistical calculations were performed using one-way ANOVA followed by the Bonferroni t-test. P-values <0.05 were considered to indicate significant differences.
Statistical calculations were performed using one-way ANOVA followed by the Bonferroni t-test using SigmaStat software (Systat Software Inc.; San Jose, USA).
Data of the fat layer thickness from pretreatment, posttreatment, and three-day follow-up were analyzed and compared by One-Way Repeated Measure ANOVA (2-sided) using SPSS 15.0 with post hoc multiple comparison test: Bonferroni t-test.
Analysis for statistical significance was performed using One-Way Repeated Measures ANOVA with post hoc multiple comparison test: Bonferroni t-test. Figure 3 highlights a statically significant reduction (p < 0.01) in the fat layer thickness between the pre-treatment and posttreatment groups, indicating that the intervention with low-intensity nonfocused ultrasound caused reduction in adipocyte thickness by inducing lipolysis.
Differences among groups were analyzed using one-way analysis ofvariance (ANOVA) for multiple comparisons and a Bonferroni t-test using SPSS statistical software.
Mean difference, standard error, levels of statistical significance in post-hoc comparisons between the 3 groups, using the Bonferroni t-test are shown in Table 2.
Statistical analysis began with a two way ANOVA using experiment as one factor, and dose as the second factor for length comparsions, followed by Bonferroni t-test multiple comparisons
tratado * P < 0,05 ANOVA test y Bonferroni t-test. SE.
EOAz, there was a significant reduction (p[less than or equal to]0.05, ANOVA, Bonferroni t-test) in the number of seconds the mice spent liking their paws in the first and second phase, which reached 22% and 93.99% (n = 10), respectively, of controls (70.4 [+ or -] 3.04 and 142.7 [+ or -] 15.09 s, n = 11) (Fig.
tratado * P<0,05 Datos parametricos; ANOVA test y Bonferroni t-test. Datos no Parametritos; Kruskal-Wallis y Mann-Whitney Utest SE.