Finding percentages from a data plot in R

Question

I am struggling with Part 1G. I used dput() here is the part of the data that is being used for this probelem:

paiddeposit = c(1L, 
0L, 1L, 1L, 0L, 0L, 1L, 1L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 
1L, 1L, 0L, 0L, 1L, 1L, 0L, 0L, 0L, 1L, 0L, 1L, 0L, 1L, 0L, 0L, 
0L, 1L, 0L, 0L, 0L, 1L, 0L, 1L, 0L, 1L, 1L, 0L, 0L, 1L, 0L, 1L, 
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
0L, 1L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 1L, 0L, 
0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 1L, 0L, 
0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 
1L, 0L, 0L, 0L, 0L, 1L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 
1L, 0L, 0L, 0L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 1L, 
1L, 1L, 0L, 1L, 0L, 0L, 1L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 1L, 1L, 
0L, 1L, 0L, 1L, 1L, 1L, 0L, 0L, 0L, 1L, 0L, 1L, 1L, 0L, 0L, 0L, 
0L, 0L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
0L, 0L, 0L, 1L, 0L, 1L, 0L, 0L, 1L, 1L, 0L, 1L, 0L, 1L, 0L, 0L, 
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 0L, 0L, 
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 
0L, 0L, 1L, 1L, 0L, 0L, 1L, 0L, 0L, 1L, 0L, 0L, 0L, 1L, 0L, 0L, 
0L, 1L, 0L, 0L, 0L, 1L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
1L, 0L, 0L, 1L, 0L, 0L, 0L, 1L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 
1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 1L, 0L, 0L, 0L, 1L, 
0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 0L, 0L, 1L, 0L, 0L, 
1L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 
0L, 0L, 1L, 0L, 1L, 0L, 0L, 1L, 1L, 0L, 0L, 0L, 1L, 1L, 0L, 1L, 
1L, 1L, 1L, 0L, 0L, 1L, 0L, 0L, 0L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 
0L, 0L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 1L, 0L, 0L, 
0L, 0L, 1L, 1L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 1L, 1L, 0L, 
1L, 0L, 1L, 0L, 0L, 0L, 1L, 1L, 0L, 1L, 1L, 0L, 0L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 1L, 1L, 0L, 
1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 
1L, 1L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 1L, 1L, 0L, 
0L, 0L, 1L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 
1L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 1L, 1L, 0L, 1L, 1L, 0L, 1L, 1L, 
1L, 1L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 1L, 
0L, 0L, 1L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 
0L, 1L, 0L, 1L, 0L, 0L, 0L, 1L, 0L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 
1L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 1L, 0L, 1L, 1L, 0L, 0L, 1L, 
0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 0L, 
1L, 1L, 1L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 1L, 0L, 1L, 0L, 0L, 0L, 
0L, 0L, 0L, 0L, 1L, 1L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 
0L, 1L, 0L, 1L, 0L, 0L, 0L, 1L, 0L, 0L, 1L, 0L, 1L, 1L, 0L, 0L, 
1L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 
0L, 1L, 1L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
0L, 0L, 0L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 
0L, 0L, 0L, 1L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 0L, 1L, 0L, 0L, 1L, 
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 1L, 1L, 
0L, 1L, 1L, 0L, 0L, 0L, 1L, 0L, 1L, 0L, 0L, 0L, 0L, 1L, 1L, 0L, 
0L, 0L, 0L, 0L, 1L, 0L, 1L, 0L, 0L, 0L, 1L, 1L, 1L, 0L, 1L, 0L, 
0L, 1L, 0L, 1L, 0L, 0L, 0L, 1L, 1L, 0L, 1L, 0L, 1L, 0L, 1L, 0L, 
1L, 1L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 0L, 0L, 1L, 0L, 1L, 0L, 
0L, 0L, 0L, 0L, 1L, 1L, 1L, 0L, 1L, 1L, 0L, 0L, 1L, 1L, 0L, 0L, 
0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 
0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 
0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 
1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 1L, 0L, 1L, 
1L, 0L, 0L, 0L, 1L, 1L, 0L, 1L, 1L, 1L, 0L, 1L, 1L, 1L, 1L), 
    scholarship_yes_no = c(0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    1L, 0L, 1L, 0L, 1L, 1L, 0L, 1L, 0L, 0L, 1L, 1L, 0L, 0L, 0L, 
    1L, 1L, 0L, 1L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 1L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 1L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    1L, 0L, 1L, 1L, 1L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 1L, 1L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 1L, 0L, 0L, 1L, 1L, 1L, 0L, 0L, 0L, 1L, 1L, 1L, 0L, 
    0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 1L, 0L, 0L, 0L, 1L, 0L, 0L, 
    0L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 1L, 0L, 0L, 1L, 
    0L, 0L, 0L, 1L, 1L, 0L, 0L, 1L, 0L, 0L, 1L, 1L, 0L, 0L, 1L, 
    0L, 1L, 0L, 1L, 0L, 1L, 1L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 
    0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 
    0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 
    0L, 0L, 0L, 1L, 0L, 1L, 0L, 0L, 1L, 1L, 0L, 0L, 1L, 1L, 0L, 
    0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 1L, 
    1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 
    1L, 1L, 0L, 1L, 0L, 0L, 0L, 0L, 1L, 0L, 1L, 0L, 1L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 1L, 0L, 
    1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 
    1L, 0L, 1L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 1L, 0L, 0L, 1L, 0L, 
    0L, 0L, 1L, 1L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 
    1L, 0L, 1L, 1L, 0L, 0L, 1L, 0L, 0L, 1L, 0L, 1L, 0L, 0L, 0L, 
    0L, 0L, 1L, 1L, 0L, 0L, 0L, 0L, 1L, 1L, 0L, 1L, 0L, 0L, 1L, 
    0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 1L, 0L, 1L, 0L, 1L, 0L, 0L, 
    1L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 1L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 1L, 0L, 1L, 0L, 0L, 0L, 0L, 1L, 0L, 1L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 1L, 0L, 0L, 1L, 1L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 1L, 0L, 1L, 0L, 0L, 0L, 1L, 1L, 1L, 1L, 0L, 1L, 
    1L, 1L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 
    0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 1L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 0L, 0L, 1L, 0L, 
    0L, 0L, 1L, 0L, 0L, 1L, 1L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 1L, 0L, 1L, 0L, 0L, 0L, 0L, 1L, 0L, 1L, 0L, 1L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 1L, 0L, 1L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 
    1L, 0L, 0L, 0L, 1L, 1L, 0L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 1L, 
    1L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 1L, 0L, 1L, 1L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    1L, 1L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 1L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 
    0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 0L, 
    0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 1L, 0L, 
    1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 1L, 0L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 
    0L, 1L, 0L, 0L, 0L, 1L, 0L, 1L, 0L, 0L, 0L, 0L, 1L, 0L, 1L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 1L, 1L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 1L, 1L, 0L, 
    0L, 0L, 0L, 0L, 1L, 0L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L), Type_of_scholarship_offered = c("", "", "", "", "", 
    "", "", "", "", "U1", "", "C6", "", "U4", "C2", "", "C4", 
    "", "", "U1", "IL", "", "", "", "HT", "C4", "", "U2", "", 
    "", "", "U2", "", "", "", "", "", "", "", "", "", "", "", 
    "", "", "", "", "", "", "", "", "U2", "", "IC", "", "", "", 
    "", "", "", "", "", "", "", "U1", "", "", "", "C6", "", "", 
    "", "", "", "", "", "", "", "", "", "", "", "", "", "U1", 
    "", "U1", "U4", "RL", "", "", "", "U1", "", "", "", "", "", 
    "", "", "", "", "RL", "U2", "", "", "", "", "U1", "", "", 
    "", "", "", "", "", "U2", "", "", "U4", "U2", "U2", "", "", 
    "", "U4", "2C", "U2", "", "", "", "", "", "", "U4", "", "", 
    "U4", "", "", "", "C4", "", "", "", "", "", "", "U6", "RL", 
    "", "", "", "", "", "", "", "", "", "", "", "U1", "C4", "", 
    "", "", "", "", "U1", "", "HT", "", "", "U1", "", "", "", 
    "U2", "U1", "", "", "U2", "", "", "U2", "U6", "", "", "IL", 
    "", "U2", "", "HT", "", "C4", "U1", "", "", "", "", "U2", 
    "", "", "", "", "", "", "", "U2", "U2", "", "", "", "", "", 
    "", "C4", "", "", "", "", "", "U2", "", "", "", "", "", "", 
    "", "", "", "", "U1", "", "", "", "", "", "U4", "HT", "U4", 
    "", "", "", "", "U2", "", "", "", "", "", "", "", "U2", "", 
    "", "", "", "", "", "U4", "", "", "", "", "", "U6", "", "HT", 
    "", "", "U4", "U4", "", "", "HT", "U4", "", "", "", "U1", 
    "", "", "", "", "", "", "", "", "IC", "", "", "HT", "C6", 
    "", "", "", "", "", "", "", "", "", "", "", "", "HT", "U2", 
    "U1", "U2", "", "C4", "", "", "", "", "U4", "", "U4", "", 
    "C4", "", "", "", "", "", "", "", "", "", "", "", "", "", 
    "U6", "", "U1", "", "U1", "U4", "", "", "", "", "", "", "", 
    "", "", "C4", "", "", "", "U4", "", "U2", "", "", "", "", 
    "U1", "", "", "U2", "", "", "U2", "", "", "", "RL", "U1", 
    "", "", "U6", "", "", "", "", "", "", "", "", "", "", "", 
    "", "", "", "", "U1", "", "", "U4", "", "", "", "", "", "", 
    "", "", "", "", "", "", "", "", "", "", "", "", "U4", "U1", 
    "", "U6", "U2", "", "", "U2", "", "", "U2", "", "U1", "", 
    "", "", "", "", "U4", "U2", "", "", "", "", "U2", "4C", "", 
    "U2", "", "", "U2", "", "", "", "", "", "U2", "", "", "U6", 
    "", "U1", "", "U2", "", "", "U4", "", "", "", "", "", "", 
    "U1", "", "", "", "", "", "", "", "", "", "", "U2", "", "", 
    "U1", "", "", "", "", "", "", "", "", "", "", "", "", "", 
    "U4", "", "C4", "", "", "", "", "U2", "", "C2", "", "", "", 
    "", "", "", "", "U1", "", "", "", "", "", "", "", "", "", 
    "U2", "", "", "U2", "U2", "", "", "U4", "", "", "", "", "", 
    "", "", "", "U4", "", "U6", "", "", "", "U1", "U1", "U4", 
    "RL", "", "U1", "U2", "RL", "", "", "C4", "", "", "", "", 
    "", "", "U6", "", "", "", "", "U4", "", "", "", "", "", "", 
    "", "", "", "", "", "", "", "", "U1", "", "", "", "", "", 
    "U4", "U2", "", "", "", "", "U1", "", "", "", "C2", "", "", 
    "U1", "U2", "", "U1", "", "", "", "", "", "", "", "", "", 
    "U4", "", "U6", "", "", "", "", "RL", "", "U6", "", "U1", 
    "", "", "", "", "", "", "", "", "", "", "", "U2", "", "", 
    "", "", "", "", "", "", "U4", "", "U1", "", "", "", "U1", 
    "U4", "", "", "U2", "", "", "", "U1", "U1", "", "U1", "U2", 
    "U4", "", "", "", "", "C6", "U1", "", "", "U4", "", "", "", 
    "", "", "", "", "", "", "", "", "", "U1", "", "U1", "U4", 
    "", "", "U4", "", "", "", "", "", "", "", "U6", "RL", "", 
    "C6", "", "", "", "", "", "", "", "", "", "", "", "", "", 
    "U1", "", "U6", "", "", "", "", "", "", "U4", "", "", "", 
    "", "", "U1", "", "", "", "", "", "", "", "U4", "", "", "", 
    "", "", "", "", "", "U2", "U4", "", "", "", "", "U2", "U4", 
    "", "", "", "", "U1", "", "", "", "", "", "", "U1", "", "", 
    "", "", "", "", "", "U4", "", "", "", "", "", "", "", "", 
    "", "U4", "", "U1", "", "U2", "", "", "", "", "", "", "", 
    "", "", "", "", "", "", "", "", "", "", "", "U4", "", "RL", 
    "IL", "", "", "", "", "", "U4", "U1", "", "U2", "", "", "", 
    "U1", "", "U6", "", "", "", "", "CG", "", "RL", "", "", "", 
    "", "", "", "", "U4", "", "U1", "U4", "", "", "", "", "", 
    "", "", "", "", "", "", "", "U4", "", "", "", "HT", "U2", 
    "", "", "", "", "", "U8", "", "RL", "U4", "", "", "", "", 
    "", "", "", ""), Female = c(0, 0, 0, 0, 0, 1, 1, 0, 0, 1, 
    0, 1, 0, 1, 0, 0, 1, 1, 1, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 
    0, 1, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 1, 1, 0, 0, 1, 1, 0, 
    1, 1, 1, 1, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 1, 1, 0, 0, 1, 
    1, 1, 0, 1, 1, 0, 0, 0, 0, 1, 1, 1, 0, 1, 1, 0, 0, 1, 0, 
    0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1, 1, 1, 
    0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 1, 1, 
    0, 1, 1, 1, 1, 1, 0, 0, 1, 0, 0, 1, 0, 0, 0, 1, 1, 0, 1, 
    1, 1, 0, 1, 1, 1, 1, 0, 1, 0, 1, 1, 1, 0, 0, 0, 0, 1, 0, 
    1, 1, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 1, 0, 1, 1, 1, 0, 
    1, 1, 1, 1, 1, 0, 0, 0, 1, 1, 0, 0, 1, 0, 0, 1, 1, 1, 1, 
    1, 0, 0, 0, 0, 1, 0, 1, 1, 1, 0, 0, 1, 0, 0, 0, 0, 1, 1, 
    0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 1, 0, 0, 1, 1, 1, 1, 0, 
    0, 0, 0, 1, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 1, 0, 1, 1, 0, 
    1, 0, 0, 1, 0, 0, 0, 1, 0, 1, 1, 0, 1, 1, 1, 1, 1, 0, 1, 
    1, 0, 0, 1, 1, 0, 0, 1, 0, 0, 1, 0, 1, 1, 0, 0, 0, 0, 0, 
    0, 0, 0, 1, 1, 1, 0, 0, 0, 1, 0, 1, 0, 1, 0, 1, 1, 1, 1, 
    0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 1, 
    0, 1, 0, 0, 1, 0, 1, 1, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 1, 
    1, 0, 1, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 1, 0, 1, 1, 0, 
    0, 0, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 1, 1, 0, 
    0, 1, 0, 0, 1, 1, 1, 0, 1, 1, 1, 0, 0, 0, 1, 1, 1, 1, 1, 
    1, 0, 0, 0, 0, 1, 0, 1, 0, 1, 0, 0, 1, 1, 1, 0, 1, 0, 0, 
    0, 1, 1, 0, 1, 0, 1, 1, 0, 0, 1, 1, 1, 1, 1, 0, 0, 0, 0, 
    0, 1, 0, 0, 1, 0, 0, 0, 1, 0, 0, 1, 1, 0, 1, 1, 1, 1, 1, 
    1, 1, 1, 0, 1, 0, 1, 1, 1, 0, 1, 0, 0, 0, 0, 1, 0, 1, 1, 
    1, 0, 1, 0, 0, 1, 0, 1, 1, 0, 0, 1, 0, 0, 0, 0, 0, 1, 1, 
    0, 1, 1, 1, 1, 0, 1, 0, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 1, 
    0, 1, 1, 0, 0, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0, 
    0, 1, 0, 0, 1, 0, 1, 0, 1, 1, 0, 0, 0, 0, 0, 1, 0, 1, 1, 
    1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 0, 0, 0, 1, 
    0, 1, 1, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 
    1, 1, 0, 1, 0, 1, 1, 0, 0, 0, 0, 1, 1, 1, 1, 1, 0, 0, 1, 
    0, 1, 0, 1, 1, 0, 1, 1, 1, 0, 1, 1, 0, 0, 0, 0, 1, 1, 0, 
    0, 1, 1, 1, 1, 1, 0, 0, 1, 1, 0, 1, 1, 0, 1, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 1, 1, 0, 1, 0, 1, 0, 0, 
    0, 0, 0, 0, 0, 1, 1, 0, 1, 1, 1, 0, 1, 1, 0, 0, 0, 1, 0, 
    1, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 1, 1, 1, 0, 1, 0, 0, 
    1, 1, 0, 1, 0, 1, 1, 0, 0, 1, 1, 1, 0, 0, 0, 1, 1, 0, 0, 
    0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 1, 0, 1, 1, 1, 0, 
    0, 1, 0, 1, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 
    0, 1, 1, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 
    1, 0, 1, 1, 1, 1, 1, 0, 0, 0, 1, 1, 1, 1, 0, 0, 1, 1, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0, 0, 0, 
    0, 1, 1, 1, 1, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0), 

Instructions Page 1

Here is my code:

---
title: "R Notebook"
output: html_notebook
---
  
  #Problem 0
  ```{r}
getwd()
cba = read.table("cba_admissions_1999.txt", sep = "\t", header = T, quote = "", allowEscapes = T)
```

#Problem 1
```{r}
#PART A
scholars <- sum(cba$scholarship_yes_no == 1)
scholars

scholar_percent = scholars/880 * 100
scholar_percent
```

```{r}
#number of students who were offered scholarships is 205 and the percentage is abou 23.3%

#PART B
females <- sum(cba$Female == 1)
females
female_scholars <- sum(cba$scholarship_yes_no == 1 & cba$Female == 1)
female_scholars
fem_scholar_percent = female_scholars / scholars *100
fem_scholar_percent

other_females <- sum(cba$scholarship_yes_no == 0 & cba$Female == 1)
other_females
fem_percent = other_females / (880 - scholars) * 100
fem_percent

#Of the students on scholarship, about 50% are women. Of the students who are not on scholarship, about 43.5% are women.
```

```{r}
#PART C
female_scholar_summary <- cba[cba$scholarship_yes_no == 1 & cba$Female == 1,]
mean(female_scholar_summary$Max_Test_Score)
sd(female_scholar_summary$Max_Test_Score)

female_summary <- cba[cba$scholarship_yes_no == 0 & cba$Female == 1,]
mean(female_summary$Max_Test_Score)
sd(female_summary$Max_Test_Score)

#The mean test score for females on scholarship is 1255.437 with SD of 105.3358 and the mean for females not on scholarship is 1095.17 with SD of 82.39
```

```{r}
#PART D
scholarships = split(cba,cba$scholarship_yes_no)
not_scholar = scholarships[["0"]]
scholar = scholarships[["1"]]
scholarships_yes_females = split(scholar, scholar$Female)
scholarships_no_females= split(not_scholar, not_scholar$Female)
scholarships_female = scholarships_yes_females[["1"]]
test_female_scholar = scholarships_female$Max_Test_Score
no_scholarships_females = scholarships_no_females[["1"]]
test_female_not_scholar = scholarships_female$Max_Test_Score

par(mfrow = c(1,2))
hist(test_female_scholar, xlab = "Max Test Score", main = "Female Students on Scholarship", ylab = "Numnber of Students" )
hist(test_female_not_scholar, xlab = "Max Test Score", main = "Female Students not on Scholarship", ylab = "Number of Students")
```

```{r}
#PART E
women = cba[cba$Female==1,]
boxplot(women$Max_Test_Score ~ women$scholarship_yes_no)
```

```{r}
#PART F
scholar_female_dist = scholarships_female$distancefromPitt
summary(scholar_female_dist)
not_scholar_female_dist = no_scholarships_females$distancefromPitt
summary(not_scholar_female_dist)
#The closer a female student lives to Pitt, the less likely she is to get a scholarship
```

```{r}
#PART G
paid_deposit_scholar = split(paid_deposit_yes, paid_deposit_yes$scholarship_yes_no)
paid_deposit_scholar = paid_deposit_scholar[["1"]]
paid_deposit_not_scholar = paid_deposit_scholar[["0"]]
paid_deposit = split(cba, cba$paiddeposit)
paid_deposit_yes = paid_deposit[["1"]]
paid_deposit_no = paid_deposit[["0"]]
female_paid_scholar = (paid_deposit_yes$scholarships_female)
length(female_paid_scholar)/length(scholarships_female)
```

My problem is that for the last problem, female_paid_scholar is NULL and the last line of code is therefore 0 even though there are in the table of data females who paid the deposit and are on scholarship.