$\backslash$table$[[,$Acquisition,Online Behavior,Purchase$],[$Gender$,$All Users,New Users,$\backslash$table$[[$Users Who$],[$Viewed$],[$Only One$],[$Page$]],\backslash$table$[[$Bounce$],[$Rate$]],\backslash$table$[[$Pages$],[$Viewed per$],[$User$]],\backslash$table$[[$User$],[$Duration $($on$],[$avg$.)$ in$],[$Seconds$]],\backslash$table$[[$Users Who$],[$Were$],[$Engaged in a$],[$Transaction$]],$REVENUE,$\backslash$table$[[$Ecommerce$],[$Conversion$],[,$ Rate$]]],[$Male$,2000,500,200,,3,90,50,$$$15,00,],[$Female$,4000,1900,400,,4,140,500,$$$35,0*0,]]$

If you drill into the target age group, what would be the bounce rates for males and females? $($Use the data in Figure $2.)$

$\backslash$table$[[,$A$,$B$,$C$,$D$,$E$,$F$],[1,$Sex,New Users,$\backslash$table$[[$Users Who$],[$Viewed Only $1],[$Page$]],$Bounce Rate,$\backslash$table$[[$Users Who Were$],[$Engaged in a$],[$Transaction$]],\backslash$table$[[$Ecommerce$],[$Conversion Rate$]]],[2,$Male,,,NaN,,NaN