Create boxplots for the variables GPA, Social Networking and Spending for male a

Question

Create boxplots for the variables GPA, Social Networking and Spending for male and female students to compare the shape and spread for these sample data of male and female students. For boxplots, you may either use Excel or Statcrunch. Are there any outliers? detail help needed, dont know how to put 3 variable in boxplots (here's the DATA below)

ID Gender Age Class Major Grad Intention GPA Employment Salary Social Networking Satisfaction Spending Computer Text Messages Wealth 1 Female 20 Sophomore Other Yes 2.88 Full-Time 55.0 5 3 850 Laptop 200 2.0 2 Male 23 Senior Management Yes 3.60 Part-Time 30.0 4 4 860 Desktop 50 10.0 3 Male 21 Freshman Other Yes 2.50 Part-Time 50.0 2 4 1100 Laptop 200 70.0 4 Male 21 Sophomore IS Yes 2.50 Full-Time 45.0 4 6 1100 Tablet 250 100.0 5 Male 23 Senior Other Undecided 2.80 Unemployed 45.0 7 4 1000 Laptop 100 1.0 6 Female 26 Senior Economics/Finance Undecided 2.34 Unemployed 83.0 3 2 1200 Desktop 0 5.0 7 Female 21 Junior Other Undecided 3.00 Part-Time 55.0 3 3 1000 Laptop 50 0.6 8 Female 30 Senior Other Undecided 3.10 Full-Time 85.0 1 2 700 Tablet 300 1.0 9 Female 20 Sophomore Management Yes 3.60 Unemployed 35.0 0 4 1000 Laptop 400 0.6 10 Female 21 Senior Economics/Finance Undecided 3.30 Part-Time 42.5 11 4 700 Laptop 100 1.0 11 Female 23 Senior Economics/Finance Yes 2.80 Full-Time 55.0 5 5 900 Laptop 200 30.0 12 Male 22 Senior Economics/Finance No 3.50 Full-Time 42.0 4 3 1000 Laptop 100 4.0 13 Male 22 Senior Marketing Undecided 3.40 Part-Time 45.0 6 3 900 Desktop 45 0.7 14 Male 22 Senior Marketing Undecided 3.10 Part-Time 45.0 1 3 900 Laptop 150 2.0 15 Male 21 Senior Management Yes 3.20 Part-Time 59.0 0 4 1100 Laptop 400 6.0 16 Male 24 Senior Management Undecided 3.40 Part-Time 50.0 4 4 1000 Desktop 175 1.5 17 Female 19 Freshman IS Undecided 3.68 Part-Time 60.0 10 4 950 Tablet 150 0.5 18 Male 21 Junior Economics/Finance Undecided 3.10 Part-Time 60.0 2 3 1100 Laptop 300 10.0 19 Male 19 Sophomore Economics/Finance Yes 3.50 Part-Time 57.0 4 5 1000 Laptop 300 2.0 20 Female 20 Sophomore Management Undecided 3.17 Unemployed 65.0 12 6 800 Laptop 350 0.4 21 Female 22 Junior Marketing Undecided 3.19 Part-Time 60.0 11 3 1190 Laptop 50 0.4 22 Male 18 Sophomore Accounting Undecided 2.95 Unemployed 65.0 9 4 1100 Laptop 500 10.0 23 Female 22 Senior Marketing Undecided 3.00 Part-Time 60.0 0 4 800 Laptop 35 0.2 24 Male 25 Senior Undecided Yes 2.60 Full-Time 50.0 8 5 900 Laptop 600 1.5 25 Female 20 Junior Economics/Finance Yes 3.00 Part-Time 60.0 7 3 1100 Laptop 300 0.1 26 Male 24 Senior Management Yes 3.30 Full-Time 65.0 0 1 800 Desktop 40 10.0 27 Male 23 Junior Economics/Finance Yes 3.10 Full-Time 70.0 4 5 875 Laptop 300 2.0 28 Female 20 Freshman Marketing Yes 2.90 Part-Time 55.0 13 1 1400 Laptop 100 1.0 29 Male 22 Senior Marketing Yes 3.33 Part-Time 60.0 9 6 1600 Laptop 60 100.0 30 Male 20 Sophomore Marketing Undecided 3.10 Part-Time 50.0 4 4 900 Laptop 140 7.0 31 Male 20 Sophomore Accounting Undecided 3.40 Part-Time 60.0 4 3 1000 Laptop 500 5.0 32 Male 20 Junior Other Yes 2.90 Part-Time 52.0 3 1 800 Laptop 300 1.3 33 Male 20 Junior Accounting Yes 3.60 Part-Time 40.0 6 4 700 Laptop 70 0.8 34 Male 22 Senior Marketing Yes 2.57 Full-Time 45.0 5 4 1550 Laptop 800 0.9 35 Female 19 Sophomore Marketing Undecided 3.40 Part-Time 45.0 4 5 1000 Laptop 300 0.1 36 Female 26 Junior Accounting Yes 3.30 Part-Time 65.0 2 4 950 Desktop 300 0.8 37 Male 21 Senior Management Yes 3.05 Part-Time 45.0 3 4 1000 Laptop 100 5.0 38 Female 21 Sophomore Accounting Yes 2.50 Part-Time 65.0 2 3 1000 Laptop 600 0.9 39 Male 24 Junior Economics/Finance Yes 2.75 Part-Time 55.0 7 6 1100 Desktop 50 1.0 40 Male 19 Freshman Marketing Yes 2.50 Unemployed 55.0 15 5 800 Laptop 100 1.0 41 Male 22 Junior Accounting Yes 3.20 Full-Time 65.0 4 4 1180 Desktop 200 0.5 42 Female 20 Junior Marketing No 3.30 Part-Time 35.0 6 4 1100 Laptop 350 1.0 43 Female 22 Senior Marketing Undecided 3.50 Unemployed 45.0 5 5 800 Laptop 50 6.0 44 Female 27 Senior Marketing No 3.90 Full-Time 35.0 4 5 600 Laptop 400 1.0 45 Female 21 Senior Marketing No 3.00 Part-Time 35.0 6 5 1150 Desktop 500 0.5 46 Female 21 Senior Management Undecided 3.82 Part-Time 65.0 1 4 1150 Laptop 150 1.0 47 Female 20 Junior Marketing Yes 3.50 Unemployed 65.0 5 3 850 Laptop 200 0.3 48 Male 19 Sophomore Undecided Undecided 2.50 Part-Time 85.0 3 4 1000 Desktop 150 3.0 49 Female 21 Senior Economics/Finance Yes 3.20 Part-Time 52.5 2 4 720 Laptop 105 1.0 50 Female 23 Sophomore Economics/Finance Undecided 3.00 Part-Time 50.0 5 3 1020 Laptop 105 0.7 51 Female 21 Junior Management No 3.50 Unemployed 40.0 1 4 1100 Tablet 100 1.0 52 Male 23 Senior Management No 3.00 Part-Time 55.0 4 4 1000 Laptop 200 5.0 53 Female 21 Senior Marketing Undecided 3.70 Part-Time 45.0 3 4 800 Laptop 700 10.0 54 Male 21 Junior Marketing No 3.40 Part-Time 45.0 7 5 1000 Laptop 300 0.5 55 Male 21 Senior Other Yes 3.40 Part-Time 55.0 3 4 750 Desktop 700 2.5 56 Female 21 Senior Marketing No 3.10 Part-Time 55.0 3 1 800 Desktop 300 3.5 57 Female 21 Senior Marketing Yes 3.40 Part-Time 47.0 6 1 700 Laptop 100 3.8 58 Female 21 Senior Marketing No 2.40 Part-Time 45.0 4 3 1500 Laptop 10 1.0 59 Female 20 Junior IS No 2.90 Part-Time 45.0 4 4 850 Laptop 250 0.1 60 Female 20 Sophomore IS No 2.50 Part-Time 60.0 7 4 1000 Tablet 500 1.0 61 Female 23 Senior Accounting Yes 3.50 Part-Time 35.0 6 3 990 Laptop 50 1.0 62 Female 23 Senior Economics/Finance No 3.20 Part-Time 75.0 2 3 750 Laptop 0 2.0 63 Male 24 Junior Economics/Finance Yes 2.70 Full-Time 70.0 6 6 570 Tablet 100 1.0 64 Male 23 Junior Economics/Finance No 3.10 Part-Time 65.0 9 4 650 Laptop 200 10.0 65 Male 18 Freshman Undecided Yes 3.60 Unemployed 55.0 12 4 700 Tablet 500 1.0 66 Male 24 Senior Management No 3.10 Part-Time 50.0 4 4 800 Laptop 0 0.9 67 Male 23 Sophomore Marketing No 2.20 Unemployed 50.0 5 4 650 Desktop 100 10.0 68 Female 22 Senior Accounting No 3.20 Part-Time 60.0 4 5 800 Laptop 100 1.0 69 Female 25 Senior Marketing Yes 2.80 Full-Time 50.0 3 2 800 Laptop 0 7.5 70 Male 26 Senior Economics/Finance Yes 3.70 Part-Time 65.0 6 3 800 Desktop 60 1.0 71 Male 19 Freshman Economics/Finance Undecided 2.60 Unemployed 60.0 9 5 800 Laptop 400 0.1 72 Female 24 Senior Management No 3.10 Part-Time 55.0 4 4 1060 Desktop 600 1.0 73 Female 20 Freshman Accounting Undecided 2.40 Part-Time 60.0 8 5 800 Laptop 5 1.0 74 Male 23 Junior IS Undecided 3.60 Part-Time 70.0 12 6 900 Laptop 10 1.0 75 Male 23 Senior Management No 3.10 Part-Time 55.0 5 6 800 Laptop 0 10.0 76 Female 28 Senior Economics/Finance Yes 3.50 Part-Time 75.0 4 6 900 Desktop 350 5.0 77 Male 25 Senior Management No 2.50 Full-Time 50.0 2 3 800 Laptop 5 0.5 78 Male 24 Senior Economics/Finance Undecided 3.40 Part-Time 60.0 3 5 1175 Laptop 60 50.0 79 Female 21 Sophomore Undecided Yes 3.30 Part-Time 55.0 6 4 900 Laptop 650 1.0 80 Female 22 Sophomore Marketing Undecided 3.00 Part-Time 50.0 5 5 1000 Laptop 200 1.5 81 Female 19 Freshman Undecided Undecided 2.80 Unemployed 50.0 8 4 850 Tablet 650 2.0 82 Male 23 Junior Economics/Finance Yes 3.60 Part-Time 65.0 5 5 680 Laptop 400 5.0 83 Male 21 Junior Management No 3.00 Part-Time 45.0 4 6 700 Laptop 20 10.0 84 Male 24 Senior IS Undecided 3.30 Part-Time 60.0 8 5 750 Laptop 5 10.0 85 Male 22 Junior Economics/Finance Yes 3.70 Part-Time 65.0 6 3 745 Laptop 250 6.0 86 Female 21 Sophomore Management Undecided 2.80 Part-Time 45.0 7 4 715 Laptop 200 10.0 87 Male 25 Senior Accounting Yes 3.40 Part-Time 55.0 2 4 850 Desktop 60 100.0 88 Female 20 Sophomore Marketing Undecided 3.10 Unemployed 50.0 3 4 575 Laptop 400 2.0 89 Female 22 Junior Marketing Undecided 2.90 Part-Time 50.0 6 4 2000 Laptop 2 5.0 90 Female 23 Sophomore Economics/Finance Yes 3.50 Part-Time 60.0 4 5 750 Laptop 500 1.0 91 Male 27 Junior Marketing Undecided 3.30 Full-Time 55.0 4 5 800 Laptop 75 10.0 92 Male 22 Junior Management Undecided 2.90 Part-Time 50.0 4 4 670 Laptop 50 0.1 93 Female 26 Senior Economics/Finance Yes 3.60 Part-Time 65.0 3 5 700 Desktop 100 5.0 94 Female 30 Senior Accounting Yes 3.80 Full-Time 65.0 3 5 800 Desktop 30 2.0 95 Female 22 Sophomore Accounting No 2.10 Unemployed 60.0 9 4 730 Laptop 50 50.0 96 Male 19 Freshman Economics/Finance No 2.80 Part-Time 55.0 7 4 650 Laptop 0 1.0 97 Male 24 Junior Accounting Undecided 3.00 Full-Time 60.0 5 4 1700 Laptop 300 1.0 98 Female 20 Sophomore Economics/Finance No 3.10 Part-Time 60.0 6 5 800 Laptop 1 5.0 99 Male 19 Freshman Economics/Finance Yes 3.80 Unemployed 65.0 7 5 900 Laptop 75 3.0 100 Male 24 Senior Other No 3.10 Part-Time 50.0 3 7 900 Desktop 100 20.0 101 Female 22 Junior Management Yes 3.20 Part-Time 50.0 4 6 860 Laptop 75 3.0 102 Male 20 Freshman Marketing No 2.70 Part-Time 45.0 7 5 640 Laptop 210 5.0 103 Male 21 Sophomore Marketing No 2.90 Part-Time 40.0 5 5 1100 Tablet 400 2.5 104 Male 23 Junior Other No 3.00 Part-Time 45.0 6 5 800 Laptop 210 10.0 105 Female 24 Senior Other No 3.20 Part-Time 45.0 8 4 690 Laptop 525 0.8 106 Female 18 Freshman Management No 2.00 Unemployed 45.0 5 4 750 Laptop 100 100.0 107 Male 26 Senior Economics/Finance No 2.90 Full-Time 55.0 4 4 850 Laptop 100 50.0 108 Female 19 Freshman Undecided Undecided 3.30 Unemployed 50.0 7 3 800 Tablet 750 20.0 109 Female 21 Sophomore Undecided Undecided 2.60 Part-Time 45.0 5 4 800 Laptop 500 50.0 110 Male 18 Freshman Accounting Undecided 3.60 Part-Time 65.0 8 5 900 Laptop 750 100.0 111 Female 21 Sophomore Accounting No 3.40 Part-Time 65.0 5 5 950 Tablet 200 75.0

Explanation / Answer

I can use R software to solve this

R command is

x=read.csv("Book1.csv")
GPA_F=x[1:55,3]
GPA_M=x[56:111,3]
SN_F=x[1:55,4]
SN_M=x[56:111,4]
SP_F=x[1:55,5]
SP_M=x[56:111,5]
par(mfrow=c(2,3))
boxplot(GPA_F, main="GPA of female")
boxplot(SN_F, main="Social Networking of female")
boxplot(SP_F,main="Spending of female" )
boxplot(GPA_M, main="GPA of male")
boxplot(SN_M, main="Social Networking of male")
boxplot(SP_M,main="Spending of male" )

Except GPA of male, all variables having minimum tow and maximum three outliers.

GPA and Spending variable for male having symmetric distribution where as social networking variable having left skewed.

GPA for female having symmetric distribution where as social networking variable having right skewed and Spending variable having left skewed

Related Questions

Navigate

• Browse (All)
• Browse C
• Subjects

---

---

Integrity-first tutoring: explanations and feedback only — we do not complete graded work. Learn more.