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.
