This analysis uses the Student Performance dataset from the UCI Machine Learning Repository, which contains information about students’ academic performance as well as demographic, social, and school-related factors. I chose this dataset because I am interested in exploring how different aspects of a student’s life may relate to their academic performance. For this assignment, I will focus on creating a smaller and more understandable dataset containing variables that may be useful for examining student performance.The original dataset is available through the UCI Machine Learning Repository
I plan to load the Student Performance data set into R and examine its structure and variables. I will select a subset of variables that may be useful for understanding student academic performance, including the final grade as the target variable. I will then rename unclear or abbreviated columns and transform coded values where necessary so that the resulting data frame is easier to understand and use for future analysis. One challenge I anticipate is determining which variables are most relevant to include while making sure that any coded values are interpreted correctly using the dataset documentation.