a) Paste the output from your randomization test here. b) What is the mean difference in credit card debt of the two groups in the original data? The mean for Males is 4032 and for Females is 3101.1. Thus the mean difference is (40323101.1) = 930.9 c) What p-value did you get in your randomization? Explain in the context of the problem what the p-value means. The p-value I got is 0.464. This means that if the population means for this two groups are not significantly different we have a 0.464 probability of observing the value of the test statistic or extreme. To put in simple p-value is the probability of getting the value of the observed test statistic or extreme. d) Do you think the data support the null hypothesis of no difference in mean credit card debt between males and females or the alternate hypothesis that there is a difference? Explain your answer. The observed p-value is really high. As we reject the null hypothesis if the p-value is small (to be precise less than the significance level). So here considering a 0.05 significance level we can see that the nul hypothesis is not rejected and thus we cant conclude that there is a difference in mean credit card debt for men and women