In this report we analyze the Students Performance in Exams dataset from Kaggle. The dataset contains exam results and demographic information for 1000 students. It records gender, race or ethnicity, parental education, lunch type, test preparation, and scores in math, reading, and writing. The objective of this analysis is to use R programming to explore the structure of the data, perform data cleaning, manipulate and reshape variables, compute summary statistics, and visualize key relationships. The focus is on understanding which factors appear related to student performance in math and how reading and writing scores correlate with math scores.