Analysis of Relative Importance of Factors Affecting the Chance of Admission of Applying to Graduate Students

Abstract

The conceptualization of statistical model: the initial characteristic of linear regression revealed by Karl Pearson lay the foundation for the exploration of Sir Francis Galton. The article discusses the concept of the linear regression model and R-square and focuses on the relationship between the chance of admission and GRE/TOFEL score by the simple linear regression between independent variables and dependent variables. The collected statistical data from Kaggle about 386 students ’ scores in an American university is fitting the linear regression. This concentrates on the evaluation of the simple linear regression and the discovery of coverage for drawbacks or solutions for the promotion of the accuracy of the relationship. In the demonstrating experiments, collected TOFEL/ GRE scores of 375 graduate students in college indicated new observation that the existence of positively related between two items by R-square while testifying model possess drawbacks and limitations in a degree. The exploration of solutions to offset the impact of these errors and omissions will be concentrated in the following.