Dark Mode
Graduate Admissions Factors Dataset
Education & Learning Analytics
Tags and Keywords
Trusted By
"No reviews yet"
Free
About
This dataset provides key information essential for assessing university admission prospects for higher studies. It contains various academic and profile-related factors such as Graduate Record Examinations (GRE) scores, Test of English as a Foreign Language (TOEFL) scores, university ratings, Statement of Purpose (SOP) and Letter of Recommendation (LOR) strengths, undergraduate Cumulative Grade Point Average (CGPA), and an indicator for research experience, alongside the crucial 'Chance of Admit'. This data is valuable for understanding the multi-faceted criteria considered in university admissions and for developing models to predict admission likelihood. It includes 400 entries, offering a robust foundation for analytical studies.
Columns
- Serial No.: A unique serial number for each entry.
- GRE Score: Scores obtained in the Graduate Record Examinations, scaled out of 340. Values typically range from 290 to 340.
- TOEFL Score: Scores obtained in the Test of English as a Foreign Language, scaled out of 120. Values typically range from 92 to 120.
- University Rating: A rating of the target university, on a scale of 1 to 5.
- SOP: Strength of the Statement of Purpose, rated on a scale of 1 to 5.
- LOR: Strength of the Letter of Recommendation, rated on a scale of 1 to 5.
- CGPA: Undergraduate Cumulative Grade Point Average, scaled out of 10. Values typically range from 6.8 to 9.92.
- Research: Indicates whether the applicant has research experience (1) or not (0).
- Chance of Admit: The estimated probability of admission, ranging from 0 to 1. Values typically range from 0.34 to 0.97.
Distribution
The dataset is provided in a CSV file format and consists of 400 individual entries or records. It comprises 9 distinct columns, detailing various admission factors and the chance of admit. All entries across all columns are valid, with no missing or mismatched data points. The file size is approximately 12.9 kB.
Usage
This dataset is ideally suited for academic research, data science projects, and educational applications. It can be used for:
- Developing predictive models for university admissions outcomes.
- Identifying the most influential factors in securing a university admission.
- Conducting statistical analysis on the relationship between applicant profiles and admission outcomes.
- Creating educational tools to advise prospective students on improving their application profiles.
- Benchmarking and evaluating machine learning algorithms, particularly for regression tasks.
Coverage
The available sources do not specify the geographic scope, time range, or demographic scope of the data. No specific notes on data availability for certain groups or years are provided.
License
CC0: Public Domain
Who Can Use It
- Data Scientists and Machine Learning Engineers: For building and testing regression models aimed at predicting admission chances.
- Academics and Researchers: To study admission trends, factor importance, and contribute to higher education research.
- University Admissions Departments: For gaining insights into applicant profiles and potential admission outcomes.
- Prospective Students and Educational Counsellors: To understand the criteria and evaluate their own profiles against historical data.
Dataset Name Suggestions
- University Admission Predictor Data
- Graduate Admissions Factors Dataset
- Higher Education Chance of Admit
- Student Profile Admission Data
- University Entry Criteria
Attributes
Original Data Source: Graduate Admissions Factors Dataset
QUALITY