Sentence examples for mean comparisons using from inspiring English sources

Multiple mean comparisons using least significant difference were computed using the significance level (p < 0.05).

A few instruments (BEFS, PIPS, STEP, SUCCEED) reported mean comparisons using common statistical test such as independent t tests, ANOVA, and chi-square.

The least significant difference (LSD) and Duncan's multiple range test (DMRT) were used for multiple mean comparisons using the SAS statistical analysis software (version 8.2; SAS Institute, Cary, NC).

Statistical significance between the groups was assessed by multiple mean comparisons using one-way analysis of variance (ANOVA) followed by a post-hoc Dunnett's test.

We determined significant mean comparisons using the Duncan's multiple range test with an α of p < 0.01 to adjust for the higher probability of type I error in multiple comparisons.

Statistical analysis was performed using STATISTICA 7.0 software for mean comparison using Tukey's test at the significance level of P < 0.05.

Statistical analysis was performed using Statistica 7.0 software (StatSoft, Inc., Tulsa, USA) for mean comparison using Tukey's test at the significance level α = 0.05.

The effect of the different peptide concentrations on T. vaginalis was evaluated by ANOVA and a mean comparison using the least significant difference (LSD) test (α = 0.05).

Data (mean ± SE) form various samples were subjected to a one-way nested analysis of variance (ANOVA) followed by the least significant difference test (LSD) for mean comparison using SPSS Statistics 17.0 (SPSS Inc., Chicago, IL, USA).

In some cases further exploration of significant interactions were completed by post-hoc individual means comparisons using the Bonferroni correction to maintain an overall (family wise) error rate of p < 0.05.

A one-way ANOVA was conducted to compare the differences in parameters in each berry group between cluster stages followed by post-hoc means comparison using Tukey's HSD test (P < 0.05).