In this case study you are going to explore university entrance examinations (YGS/LYS) data from 2017. You are going to work with your project groups. (If you don’t have a group, form one by adhering to the project guidelines.) Report your RMarkdown output html files at the group progress journals.

Brief: Suppose, MEF University management asks you to examine the data and provide insights that are useful to understand MEF University’s place among its competitors and in the undergraduate market. Our technical team cleaned up the data for you as best as they can (you can check the raw data from here). Data is provided with the following commands and necessary information can be found below. You should explicitly state your code and process with clear communication. Assume management knows a bit of R and would like to reproduce your work in case there is any problem with the calculations. The university is not interested in universities abroad (IDs that start with 3 or 4).

The Data

# First set your working directory
setwd("~/myBDAgroup/case_1/")
# Download from GitHub (do it only once)
download.file("https://mef-bda503.github.io/files/osym_data_2017.RData", 
    "osym_data_2017.RData")
# Install tidyverse if not already installed
if (!("tidyverse" %in% installed.packages())) {
    install.packages("tidyverse", repos = "https://cran.r-project.org")
}
# Load tidyverse package
library(tidyverse)
# Load the data
load("osym_data_2017.RData")

Now that we loaded it, let’s see the data. Your data consists of undergraduate programs offered in 2017. Each program offers an availability (i.e. quota). Then students get placed according to their lists and their scores. Each program is filled with the students ranked by their scores until placements are equal to availability. Student placed to a a program with the highest score forms the maximum score of that program and the last student to be placed forms the minimum score.

Valedictorians (i.e. best students of each high school) are sometimes considered separately. Though valedictorian quota can be transferred to general availability if number of valedictorians asking for that program is fewer than valedictorian quota. (Hence for some programs general_placement > general_availability).

Now let’s see the data in detail.

glimpse(osym_data_2017)
## Observations: 11,031
## Variables: 14
## $ program_id        <int> 100110266, 100110487, 100110724, 100130252, ...
## $ university_name   <chr> "ABANT İZZET BAYSAL ÜNİVERSİTESİ", "ABANT İZ...
## $ city              <chr> "BOLU", "BOLU", "BOLU", "BOLU", "BOLU", "BOL...
## $ faculty_name      <chr> "Bolu Sağlık Yüksekokulu", "Bolu Turizm İşle...
## $ program_name      <chr> "Hemşirelik", "Gastronomi ve Mutfak Sanatlar...
## $ exam_type         <chr> "YGS_2", "YGS_4", "YGS_6", "YGS_6", "MF_3", ...
## $ general_quota     <int> 150, 60, 60, 60, 80, 1, 40, 60, 60, 80, 60, ...
## $ general_placement <int> 150, 60, 62, 26, 80, 1, 9, 62, 60, 81, 60, 7...
## $ min_score         <dbl> 328.8790, 346.4491, 225.7170, 199.2710, 446....
## $ max_score         <dbl> 376.3817, 388.3141, 290.2683, 234.9510, 451....
## $ val_quota         <dbl> 4, 2, 2, 2, 2, 0, 1, 2, 2, 2, 2, 2, 2, 3, 2,...
## $ val_placement     <dbl> 4, 2, 0, 0, 2, 0, 0, 0, 2, 1, 2, 2, 2, 3, 1,...
## $ val_min_score     <dbl> 312.8462, 293.6994, 180.0000, 180.0000, 437....
## $ val_max_score     <dbl> 328.0626, 328.7560, 180.0000, 180.0000, 442....

Your Submissions

You should submit to your group’s progress journal. Get the link at the lecture hours. Make the first submission until the end of the lecture (21:30 PM) and full submission until this Saturday, Oct 28, 7PM. Evaluation will be based on your process, your insights and your communication (i.e. storytelling).