1. Data Source:

Synthetic data generated from the Wharton Class of 2025's statistics.

2. Meta Data:

• application_id: Unique identifier for each application
• gender: Applicant's gender (Male, Female)
• international: International student (TRUE/FALSE)
• gpa: Grade Point Average of the applicant (on 4.0 scale)
• major: Undergraduate major (Business, STEM, Humanities)
• race: Racial background of the applicant (e.g., White, Black, Asian, Hispanic, Other / null: international student)
• gmat: GMAT score of the applicant (800 points)
• work_exp: Number of years of work experience (Year)
• work_industry: Industry of the applicant's previous work experience (e.g., Consulting, Finance, Technology, etc.)
• admission: Admission status (Admit, Waitlist, Null: Deny)

3. Usage:

• Exploratory Data Analysis (EDA): Understand the distributions, relationships, and patterns within the data.
• Classification: Predict the admission status based on other features.

Feel free to leave comments on the discussion. I'd appreciate your upvote if you find my dataset useful! 😀