Yusuf Bora Çavdar’s Analytics Lab
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  • Project Phase 1
    • Decoding Higher Education
  • Project Overview
  • Problem Statement & Motivation
  • Data Strategy & Sources
    • Primary Source
    • Extraction Tool
    • Core Variables
    • Temporal Coverage
  • Proposed Methodology
    • Analytical Workflow
  • Preliminary Timeline
  • Research Contributors
    • Yusuf Bora Çavdar
    • Onur Furkan Gök

Project Phase 1

Decoding Higher Education

A Trend Analysis of Industrial Engineering Programs in Turkey

Project Overview

This project investigates the structural and institutional factors shaping the success of Industrial Engineering departments across Turkey between 2018 and 2025.

Rather than treating placement statistics as isolated yearly figures, we aim to construct an integrated analytical framework capable of identifying the underlying drivers of academic prestige, student demand, and regional competitiveness.

Problem Statement & Motivation

While university placement statistics are publicly available, there is often a lack of analytical perspective explaining why certain departments consistently outperform others in national rankings.

As Industrial Engineering students, our objective is to apply modern data analytics methodologies directly to our own academic domain.

We aim to identify the underlying drivers of success and regional demand for Industrial Engineering departments across Turkey over recent years.

Data Strategy & Sources

Primary Source

  • YÖK Atlas – Lisans Atlası

Extraction Tool

  • thestats R Package
    Developed by M. Çavuş and O. Aydın

Core Variables

  • National base rankings
  • Program quotas
  • Demand ratios
  • Faculty indicators
  • Erasmus mobility
  • Student regional origins

Temporal Coverage

  • 2018 – 2025

Proposed Methodology

The analysis is implemented using R (thestats, tidyverse, ggplot2) and reported through Quarto for full reproducibility.

Analytical Workflow

  • Data extraction and harmonization
  • Missing value handling and preprocessing
  • Exploratory Data Analysis (EDA)
  • Trend analysis and sector benchmarking
  • Correlation modeling
  • Interactive visualization and reporting

Preliminary Timeline

Phase Planned Activities
Weeks 1–2 Data extraction, cleaning, preprocessing
Weeks 3–4 EDA, trend analysis, correlation modeling
Week 5 Final reporting, visualization refinement, presentation

Research Contributors

Yusuf Bora Çavdar

Data Engineering · Visualization · Statistical Analysis

Portfolio:
https://emu-hacettepe-analytics.github.io/emu430-spring2026-boracavdar/


Onur Furkan Gök

Research Design · Data Processing · Methodological Development

Portfolio:
https://emu-hacettepe-analytics.github.io/emu430-spring2026-onurfgg/

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Hacettepe IE - EMU430 - 2026 Spring