We used the data from https://www.lock5stat.com/datapage3e.html
I propose the folliwng 10 questions based on my own understanding of data.
We will explore the questions in detail.
college = read.csv("https://www.lock5stat.com/datasets3e/CollegeScores4yr.csv")
head(college)
## Name State ID Main
## 1 Alabama A & M University AL 100654 1
## 2 University of Alabama at Birmingham AL 100663 1
## 3 Amridge University AL 100690 1
## 4 University of Alabama in Huntsville AL 100706 1
## 5 Alabama State University AL 100724 1
## 6 The University of Alabama AL 100751 1
## Accred
## 1 Southern Association of Colleges and Schools Commission on Colleges
## 2 Southern Association of Colleges and Schools Commission on Colleges
## 3 Southern Association of Colleges and Schools Commission on Colleges
## 4 Southern Association of Colleges and Schools Commission on Colleges
## 5 Southern Association of Colleges and Schools Commission on Colleges
## 6 Southern Association of Colleges and Schools Commission on Colleges
## MainDegree HighDegree Control Region Locale Latitude Longitude AdmitRate
## 1 3 4 Public Southeast City 34.78337 -86.56850 0.9027
## 2 3 4 Public Southeast City 33.50570 -86.79935 0.9181
## 3 3 4 Private Southeast City 32.36261 -86.17401 NA
## 4 3 4 Public Southeast City 34.72456 -86.64045 0.8123
## 5 3 4 Public Southeast City 32.36432 -86.29568 0.9787
## 6 3 4 Public Southeast City 33.21187 -87.54598 0.5330
## MidACT AvgSAT Online Enrollment White Black Hispanic Asian Other PartTime
## 1 18 929 0 4824 2.5 90.7 0.9 0.2 5.6 6.6
## 2 25 1195 0 12866 57.8 25.9 3.3 5.9 7.1 25.2
## 3 NA NA 1 322 7.1 14.3 0.6 0.3 77.6 54.4
## 4 28 1322 0 6917 74.2 10.7 4.6 4.0 6.5 15.0
## 5 18 935 0 4189 1.5 93.8 1.0 0.3 3.5 7.7
## 6 28 1278 0 32387 78.5 10.1 4.7 1.2 5.6 7.9
## NetPrice Cost TuitionIn TuitonOut TuitionFTE InstructFTE FacSalary
## 1 15184 22886 9857 18236 9227 7298 6983
## 2 17535 24129 8328 19032 11612 17235 10640
## 3 9649 15080 6900 6900 14738 5265 3866
## 4 19986 22108 10280 21480 8727 9748 9391
## 5 12874 19413 11068 19396 9003 7983 7399
## 6 21973 28836 10780 28100 13574 10894 10016
## FullTimeFac Pell CompRate Debt Female FirstGen MedIncome
## 1 71.3 71.0 23.96 1068 56.4 36.6 23.6
## 2 89.9 35.3 52.92 3755 63.9 34.1 34.5
## 3 100.0 74.2 18.18 109 64.9 51.3 15.0
## 4 64.6 27.7 48.62 1347 47.6 31.0 44.8
## 5 54.2 73.8 27.69 1294 61.3 34.3 22.1
## 6 74.0 18.0 67.87 6430 61.5 22.6 66.7
mean(college$Enrollment, na.rm = TRUE)
## [1] 4484.831
The mean enrollment is 4484.83 students per college.
sd(college$AvgSAT, na.rm = TRUE)
## [1] 128.9077
The Standard deviation of the Average SAT score of Students at colleges is 128.9077
var(college$Cost, na.rm = TRUE)
## [1] 233433900
The Varience of the cost of to all the colleges in the data sheet is 233433900
hist(college$MidACT, main = "Histogram of Median ACT Scores", xlab = "Median ACT Score")
The most common Median ACT score of students at colleges is 22-24
median(college$Black, na.rm = TRUE)
## [1] 7.4
The median percentage of Black Students at colleges is 7.4 percent
median(college$AvgSAT, na.rm = TRUE)
## [1] 1121
The median average SAT score across all colleges is 1121.
cor(college$AdmitRate, college$MidACT, use = "complete.obs")
## [1] -0.4227796
The correlation between the admission rate and the average SAT score is -0.4227796
avg_white_by_region <- aggregate(White ~ Region, data = college, FUN = mean, na.rm = TRUE)
barplot(avg_white_by_region$White,
names.arg = avg_white_by_region$Region,
main = "Average Percentage of White Students by Region",
xlab = "Region",
ylab = "Average % of White Students",
col = "skyblue",
border = "white")
hist(college$Pell, main = "Histogram of College Pell Grant", xlab = "Pell")
boxplot(Cost ~ Control, data = college,
main = "Tuition Cost by College Type",
xlab = "College Type",
ylab = "Tuition Cost ($)",
col = c("lightblue", "lightgreen"))
Tuition is the highest among private colleges with a average tuition of
around 40 thousand, while public colleges are around half the tuition of
private colleges on average.
In conclusion, we answered all the questions that we came up with, used many different methods from Chapter 6, and learned about posit.