A practical guide to bootstrapping descriptive statistics, correlations, T tests, and anovas

This chapter provides a practical and detailed account of how to run, interpret, and report bootstrapped analyses. Because of their frequency of use in the field, that focuses on four types of analyses/statistics: descriptives, t tests, ANOVAs, and correlations. These bootstrapped analyses are accompanied with confidence interval(CIs) for the statistic of interest. The chapter also explains bootstrapping that has the potential to be a powerful nonparametric analytical tool when L2 researchers faces with problems such as small samples and nonnormal distributions. It reports bias corrected and accelerated(BCa) intervals from both SPSS and the boot package in R. In the SPSS examples, all bootstrapped analyses have been performed using the simple resampling method. The procedure jackknife-after-boot, useful for investigating the effect of outliers on the bootstrapped calculations. This chapter also focuses for a diminished role of the flawed and unreliable practice of statistical significance testing and instead for a greater emphasis on descriptive statistics-namely means, standard deviations, CIs, and effect sizes.