STAT 353 Project 1: Exploring College Data

Analysis

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

Q1: What is the mean of cost for all the colleges in the data?

mean(college$Cost, na.rm = TRUE)

## [1] 34277.31

The mean cost for the colleges in the data is $34,277.31.

Q2: What is the correlation between cost and average SAT score?

cor(college$Cost, college$AvgSAT, use = "complete.obs")

## [1] 0.5373884

The correlation between cost and average SAT score for the colleges in the data is about 0.537.

Q3: What is the distrubution of cost?

hist(college$Cost, main = "Histogram of Cost", xlab = "Cost", col = "red")

The distrubution of cost for the colleges in the data is shown in the histogram above.

Q4: What is the average admission rate for all the colleges in the data?

mean(college$AdmitRate, na.rm = TRUE)

## [1] 0.6702025

The average admission rate for the colleges in the data is about 67%.

Q5: What is the correlation between admission rate and completion rate?

cor(college$AdmitRate, college$CompRate, use = "complete.obs")

## [1] -0.3482341

The correlation between admission rate and completion rate for the colleges in the data is about -0.348.

Q6: What is the average percentage of part-time students?

hist(college$PartTime, main = "Distribution of Part-Time Students", xlab = "Percent Part-Time", col = "blue")

The average percentage of part-time students for the colleges in the data is shown in the histogram above.

Q7: What is the standard deviation of average student debt among all the colleges in the data?

sd(college$Debt, na.rm = TRUE)

## [1] 5360.986

The standard deviation of average student debt among the colleges in the data is about $5,360.99.

Q8: What is the variance in faculty salaries across all the colleges in the data?

var(college$FacSalary, na.rm = TRUE)

## [1] 6568988

The variance in faculty salaries across the colleges in the data is 6568988, which is large.

Q9: Which control type (Public, Private, or Profit) has the highest average tuition cost?

tapply(college$Cost, college$Control, mean, na.rm = TRUE)

##  Private   Profit   Public 
## 41350.33 28861.96 21338.61

The control type that has the highest average tuition cost for the colleges in the data is private at $41,350.33, followed by profit at $28,861.96, and then public at $21,338.61.

Q10: What is the relationship between median family income and average net price?

cor(college$MedIncome, college$NetPrice, use = "complete.obs")

## [1] 0.5151298

The relationship between median family income and average net price for the colleges in the data is about 0.515.