Evaluating Significance of Findings 2
Evaluating Significance of Findings Scenario 2
The sample size for this scenario can be expressed as 36 Europeans, 23 African Americans, and 18 Hispanics. Performance calculations must be performed before the start of the
course. Post-hoc calculations may be reported when a priori calculations are omitted, but their value is limited by the incorrect assumption that sample effect sizes represent population effect sizes (Sullivan & Feinn, 2012). Suppose you are comparing the means of three groups that are independent of each other and satisfy the assumptions of normality and equal variances. In that case, pairing each group with another group and making three pairwise comparisons will result in a Type I error. Often increases (Kim, 2017).
Furthermore, when testing for statistical significance, sample size and p-values imply no significant racial disadvantage in educational attainment based on studies with small sample sizes, providing erroneous conclusions. Statistical significance reflects the influence of chance on the outcome, and clinical significance reflects the clinical value of the outcome (Riemann & Liner, 2015). Using the statistical power of the data cannot extrapolate such a bold statement to all three populations, and it lacks validity. Information provided in this way is a source of misinformation and often masks the disadvantages in certain groups.
Scenario 4
Evaluating the sample size of 432 employees in the public, private, and nonprofit sectors,
it is clear that the P value is more significant than an alpha value of 0.
05, the observed variance is explained by sample variation (Sullivan & Feinn, 2012).
). Based on the sample size, the size reflects the appropriate P value for the analysis.
