The data is based on the following journal article, referenced by Samuels, et al. Ware, J. H. (1989). Investigating therapies of potentially great benefit: ECMO. Statistical Science, 298-306. http://www.jstor.org/stable/2245829?seq=1#page_scan_tab_contents Extracorporeal membrane oxygenation (ECMO) is a procedure that can be used to treat newborn babies who suffer from severe respiratory failure. An experiment was conducted in which 29 babies were treated with ECMO and 10 babies were treated with conventional medical therapy (CMT). The outcomes of this study are shown here: Treatment: CMT Treatment: ECMO Total Outcome: Die 4 1 5 Outcome: Live 6 28 34 10 29 39 More recently, ECMO has also been used in adults with respiratory failure caused by COVID-19. Randomization test Perform a randomization test (with 10000 randomizations) to test if ECMO is more effective at saving the lives of newborn babies with respiratory failure. You'll need to generate the vector of TRUE/FALSE values on your own. Include the hypotheses and conclusions. Comparison to Fisher's Exact Test https://en.wikipedia.org/wiki/Fisher%27s_exact_test https://stat.ethz.ch/R-manual/R-patched/library/stats/html/fisher.test.html Use R's fisher.test() function to conduct a Fisher exact test. How does your p-value of the Fisher Exact test compare to the results of the randomization test? Use the same null and alternative hypotheses as used for the randomization test.