Supe 1. Summarize the Wage dataset using diml). str(), and summary #R-code: dime), strand summary(run line 101-103) dim(Wage) (1) 30 11 > str Wage) data frame': 3000 obs. of Il variables 5 yearint 2006 2004 2003 2003 2005 2008 2009 2008 2006 2004 sint 18 24 45 43 50 54 44 504152 Smarit Factor w/S levels "I Never Married".-1122422 Srce Factor w/ 4 levels "L. White","2 Black":111311 5 education : Facter w/ Slevels "1. summary Wage) year are Min. -2003 Min. -18.00 1. Never Marria: 648 White 2480 1st Qu. 2004 Ist Ou:33.75 2. Married 2074 2. Black, 293 Median 2006 Median 42.00 3. Widowed 19 3. Aan 190 Meant 2006 Mean 42.41 4. Divorced 2014 Other 37 3rd Qu. 2008 3rd Qu. 51.00 5. Separated 35 Max 2009 Max. 80.00 education region 1. str Wage) data frame': 3000 obs. of Il variables 5 yearint 2006 2004 2003 2003 2005 2008 2009 2008 2006 2004 sint 18 24 45 43 50 54 44 504152 Smarit Factor w/S levels "I Never Married".-1122422 Srce Factor w/ 4 levels "L. White","2 Black":111311 5 education : Facter w/ Slevels "1. summary Wage) year are Min. -2003 Min. -18.00 1. Never Marria: 648 White 2480 1st Qu. 2004 Ist Ou:33.75 2. Married 2074 2. Black, 293 Median 2006 Median 42.00 3. Widowed 19 3. Aan 190 Meant 2006 Mean 42.41 4. Divorced 2014 Other 37 3rd Qu. 2008 3rd Qu. 51.00 5. Separated 35 Max 2009 Max. 80.00 education region 1.