Relative Power Performance of t-test and Bootstrap Procedure for Two-Sample

The classical procedures of comparing two groups, such as t-test are, usually restricted with the assumptions of normality and equal variances. when these assumptions are violated, the rates of the type i errors of the independent samples t-test are affected, particularly when the sample sizes are small. in this situation, the bootstrap procedure has an advantage over the parametric t-test. in this study, the performances of the bootstrap procedure and the independent sample t-test were investigated. the investigation focused on the power of both the test procedures to compare the two groups under different design specifications for normal and chi-square distributions. the results showed that the bootstrap procedure has a slight edge over the conventional t-test in term of the rate of achieving the benchmark level for both the distributions. in fact, the bootstrap procedure consistently outperformed the conventional t-test across all the combinations of the test conditions