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Description:

This dataset is created for prediction of Graduate Admissions from an Indian perspective.

Variables:

The dataset contains several parameters which are considered important during the application for Masters Programs.
The parameters included are :

  1. GRE Scores ( out of 340 )

  2. TOEFL Scores ( out of 120 )

  3. University Rating ( out of 5 )

  4. Statement of Purpose and Letter of Recommendation Strength ( out of 5 )

  5. Undergraduate GPA ( out of 10 )

  6. Research Experience ( either 0 or 1 )

  7. Chance of Admit ( ranging from 0 to 1 )

Link To Google Sheets:

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License Type:

References/Notes/Attributions:

 

Acknowledgments

This dataset is inspired by the UCLA Graduate Dataset. The test scores and GPA are in the older format.
The dataset is owned by Mohan S Acharya.

Citation

Please cite the following if you are interested in using the dataset :
Mohan S Acharya, Asfia Armaan, Aneeta S Antony : A Comparison of Regression Models for Prediction of Graduate Admissions, IEEE International Conference on Computational Intelligence in Data Science 2019

I would like to thank all of you for contributing to this dataset through discussions and questions. I am in awe of the number of kernels built on this dataset. Some results and visualisations are fantastic and makes me a proud owner of the dataset. Keep em' coming! Thank You.

R Dataset Upload:

Use the following R code to directly access this dataset in R.

d <- read.csv("https://www.key2stats.com/Graduate_Admission_2_1610_55.csv")
d <- read.csv("https://www.key2stats.com/Graduate_Admission_2_1610_28.csv")

R Coding Interface:


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