I am fairly new to statistics. The concept of bootstrapping has been confusing to me.
I know that normality of the sampling distribution is required to use certain tests such as the t-test. In cases when the data are not normally distributed, by requesting "bootstrapping" in t-tests in SPSS would this circumvent the problem of non-normality? If so, is the t-statistic that is reported in the output based upon the bootstrapped sampling distribution?
Also, would this be a better test compared to using non-parametric tests like Mann-Whitney or Kruskal-Wallis in cases where I have non-normal data? In situations when the data are not normal and I am using bootstrap I would not report the t-statistic: right?