Analysing a whole class' CGPA and registered credit hours in college. The data was origanally collected from real college students scores and obtained credit hours in a text form containing the IDs, registered credit hours and the CGPA of the students. Then it was converted into excel using a simple python script, after that, it was further organized into an excel workbook adding the name and the gender for each students using another sheet.
The Data used in this project is found in the excel woorkbook named class_data.xlsx which contain 2 sheets.
The main sheet contains 248 enteries each represent a student with the following columns:
- ID: Unique college ID.
- Hours_Taken: Total credit hours each student has completed up to senior year.
- CGPA: Cumulative GPA of the student at senior year.
- Gender: Gender of the student, M for male, F for female
- Name: Name of the student.
The second sheet contains ID, Gender and Name columns. This sheet is the look up table for the main sheet.
At first before we get into the details, a quick analysis of the data will get us the following information:
- Average (Mean) CGPA of the class = 2.973
- Maximum CGPA of the class = 3.76
- Minimum CGPA of the class = 1.98
- Average (Mean) completed credit hours = 130
- Maximum completed credit hours = 135
- Minimum completed credit hours = 115
We Notice that the distibution of the class' CGPA is as following
As seen above most students lie around 3 CGPA with around third of students lie between 2.9 and 3.2
Now we are interested in categorizing the students into 4 tiers:
- Tier 1 (Excellent) : Students who got a CGPA equal to 3.3 or more
- Tier 2 (Very Good) : Students who got a CGPA between 3.3 and 2.7
- Tier 3 (Good) : Students who got a CGPA between 2.7 and 2.3
- Tier 4 (Ok) : Students who got a CGPA between 2.3 and 1.7
As shown above, we conclude that two thirds of students lie in tier 2.
First we get the distribution among the class
We notice that most of the students (around 67%) completed 133 credit hours up to senior year.
Here we notice that students who completed less than average (130) credit hours have a lower average CGPA than students who completed 130 credit hours or more. We also notice one outlier who completed less than average credit hours, yet scored an excellent CGPA.
This might have happened due to many reasons such as scoring a GPA less 2 in any semester will lead to the student registering less credit credit hours the following semester, but determining whether that's the case or not will require more data such previous semesters GPA.
The count of genders in the class is as follows:
█████████████ - 160 (64.52%) Males
███████ - 88 (35.48%) Females
Mean CGPA for male studens = 2.987
Mean CGPA for female studens = 2.949
Looking at the above violin plot, we notice that male students' CGPA are more condensed around 3, while the female students' CGPA are more spread out having more range.
We conclude that roughly the distribution of male students and female students doesn't change much in both CGPA Ties and completed credit hours.
To get a more detailed look at male students data and female students data we plot a scatter graph for CGPA and completed credit hours for both male and female studetns.