Abstract—Quality education is essential for socio-economic growth, better standards of living and advances in technology. There are numerous ranking systems globally that rank university on the quality of overall education imparted by them. Our work involves Exploratory Data Analysis of the datasets of three of these ranking systems. The inferences from this shall be used to identify trends/biases in these ranking systems. Relation of the rank with various parameters and scores used by the ranking system shall also be identified. Using the aggregate score over past years a predictive model shall be trained to predict future rankings using the principles of regression.

Project Report

EDA and Predictive Analysis for NIRF Rankings

EDA and Predictive Analysis for ARWU Rankings

EDA and Inferences for QS Rankings

• Asif Shaikh
• Kalp Vyas
• Rohan Rajesh Kalbag