wage	Wage Level	gender
769	Low	Female
1583	High	Male
825	Low	Male
650	Low	Male
562	Low	Male
1400	High	Male
600	Low	Male
1081	High	Male
1154	High	Male
1000	Low	Male
930	Low	Male
921	Low	Male
900	Low	Male
1318	High	Male
1792	High	Female
958	Low	Female
1360	High	Female
850	Low	Male
830	Low	Male
471	Low	Female
1275	High	Female
1615	High	Male
873	Low	Female
2137	High	Male
1053	Low	Male
1602	High	Male
1188	High	Male
800	Low	Male
1417	High	Male
635	Low	Male
1000	Low	Female
1424	High	Male
2668	High	Female
666	Low	Male
1779	High	Female
782	Low	Male
1572	High	Male
1274	High	Female
714	Low	Male
1081	High	Male
692	Low	Male
1318	High	Male
1239	High	Male
1027	Low	Male
1748	High	Female
981	Low	Male
770	Low	Male
1154	High	Female
1155	High	Male
808	Low	Male
1100	High	Female
1154	High	Female
1749	High	Female
1000	Low	Female
462	Low	Female
769	Low	Female
875	Low	Female
1375	High	Female
1452	High	Male
800	Low	Female
1748	High	Female
1151	High	Male
840	Low	Male
978	Low	Female
963	Low	Male
619	Low	Male
442	Low	Male
600	Low	Male
1366	High	Female
1643	High	Male
1455	High	Male
2310	High	Male
1682	High	Male
1235	High	Female
855	Low	Female
1072	Low	Male
1040	Low	Female
1000	Low	Male
675	Low	Male
1100	High	Female
996	Low	Male
732	Low	Female
1200	High	Female
1694	High	Male
686	Low	Female
754	Low	Male
857	Low	Female
832	Low	Female
579	Low	Female
672	Low	Male
2500	High	Male
1076	Low	Male
750	Low	Female
1186	High	Male
833	Low	Female
650	Low	Female
1250	High	Female
1122	High	Male
865	Low	Female
808	Low	Female
1299	High	Female
903	Low	Female
900	Low	Male
625	Low	Female
1586	High	Female
962	Low	Female
1539	High	Male
1110	High	Female
1282	High	Male
770	Low	Female
1000	Low	Male
895	Low	Male
1205	High	Male
750	Low	Male
654	Low	Female
601	Low	Male
600	Low	Female
433	Low	Male
1188	High	Male
635	Low	Male
1225	High	Male
1151	High	Male
865	Low	Female
1031	Low	Male
1049	Low	Female
1000	Low	Female
1105	High	Female
1924	High	Male
1346	High	Male
809	Low	Male
1495	High	Male
1346	High	Female
1200	High	Male
500	Low	Female
1325	High	Male
900	Low	Male
800	Low	Female
800	Low	Male
1034	Low	Female
980	Low	Female
884	Low	Male
480	Low	Male
923	Low	Female
513	Low	Male
1105	High	Female
1193	High	Female
2771	High	Male
779	Low	Male
950	Low	Male
1394	High	Female

1. You want to explore the relationship between gender and wages, but they are different types of variables. To work with both, you decide to create a categorical variable based on wage levels. Explain how you determined the threshold value for this variable and present it using an appropriate graph. Then, create a graph to show the relationship between gender and the new wage variable and discuss what it shows. Use a contingency table to calculate joint and marginal probabilities for the two variables, and determine the probability of being female or having a low wage level, as well as the conditional probability of being female given a low wage level. Finally, based on the sample information, determine whether the statement "Males tend to receive high wages than females" is true, false, or inconclusive, and provide an explanation for your answer. 2. Assume that the average monthly wage for young employees in Tasmania in the year before the survey was conducted was $900. a. Perform a hypothesis test to determine if the average monthly wage of young employees in Tasmania during the year of the survey is the same as the population average wage of the previous year. b. Construct a confidence interval at the 95% level to estimate the population average wage, and interpret whether the population average wage in the year of the survey is equal to that of the previous year.