Gasoline refineries are constantly trying to differentiate their fuels from others on the market ...

     Gasoline refineries are constantly trying to differentiate their   fuels from others on the market. One way they do this is to develop gasoline   additives that are designed to improve fuel efficiency or to clean the engine   while driving. CarGo refinery has recently developed a new additive that is   expected to be the best detergent additive on the market. The breakthrough   technology has shown its ability to clean the engine during heavy   acceleration to be particularly strong.   However,   one of the product developers is concerned that this new additive might have   a negative effect on fuel efficiency. CarGo would like the gasoline treated   with the new additive to offer comparable fuel efficiency to gasoline without   the additive. To compare fuel efficiency, CarGo has filled the tanks of 50   cars with the new treated gasoline and another 50 cars with an untreated   version of the same gasoline. The data, in L/100Km, has been collected and   provided to you.   Managerial   Report:   1) Provide   a table of descriptive statistical summaries of the data for each gasoline   type and discuss any initial observations.   2) Provide   95% confidence intervals for the two types of gasoline.   3) Develop   a test that CarGo could use to address the researchers concern. Use a 0.03   level of significance.   4) Analyze   the data to provide a conclusion for your test. Provide the p-value for your   test and discuss your findings.  

     Untreated Treated   9.46637396 10.0077325   10.0843008 7.15692126   10.0998038 7.2017728   12.3540957 8.55534471   12.0583676 6.08317512   10.8302332 9.01668889   7.27974319 11.5987439   7.24443699 7.20814251   6.88841524 10.7230937   6.28002769 12.2921162   6.26767579 9.90261058   11.3033314 7.39962036   10.1517329 6.05472137   8.0530364 9.16140862   6.24940609 2.4426089   7.99990732 13.4664666   8.93848661 7.41263649   7.75781117 10.2365342   9.85940202 10.1196514   6.0841877 7.21695204   11.15212 11.7057886   9.2031294 9.64140923   5.17111274 11.8223013   7.97238974 10.0121387   8.45225899 12.2879525   6.35089669 13.1833654   11.906229 12.7398849   11.3242555 7.21551834   5.91347868 6.81395828   5.54464235 11.8913344   6.67020131 3.92675378   11.3054225 7.58473701   8.0385986 11.3059682   9.26037229 10.3590073   11.3939961 9.62595404   9.79057213 6.91912645   6.78592886 5.68956175   9.95245756 9.64626338   12.3310369 11.9981139   11.9900625 9.37492873   6.75547061 11.0772168   8.87869395 11.9090097   8.82558617 9.12805162   8.37815245 5.88136995   5.06718483 6.76454334   7.59774604 8.9970715   7.70742604 11.2629608   8.08611894 12.3552663   7.88210514 10.376194   6.09949593 8.10565901