# data science with r

project 1

Problem Statement:

An education department in the US needs to analyze the factors that influence the admission of a student into a college.

Analyze the historical data and determine the key drivers. Analysis information:

Predictive â€¢ Run logistic model to determine the factors that influence the admission process of a student (Drop insignificant variables) â€¢ Transform variables to factors wherever required â€¢ Calculate accuracy of the model â€¢ Try other modeling techniques like decision tree and SVM and select a champion model â€¢ Determine the accuracy rates for each model â€¢ Select the most accurate model â€¢ Identify other Machine learning or statistical techniques that can be used

Descriptive â€¢ Categorize the grade point average into High, Medium, and Low (with admission probability percentages) and plot it on a point chart. â€¢ Cross grid for admission variables with GRE Categorization is shown below:

GRE Categorized 0-440 Low 440-580 Medium 580 + High

Variables in the Dataset:

project 2