The data is in the below link

https://archive.ics.uci.edu/ml/datasets/Student+Performance

Data set description: This data set contains 649 rows and 33 features. The response variable is final grade(Math and Pro both). The predictors are student information, such as school, sex, age, family size, parent's education, etc. Use R-studio to conduct a linear regression analysis on the data to find out what features(maybe more than one) could impact student performance the most?

Besides programming, please write a page of complete, clear description of the analysis you performed. This should be sufficient for someone else to run an R program to reproduce your results. It should also likely be helpful to people who read your code later. This section should tie your computations to your questions/hypotheses, indicating exactly what results would lead you to what conclusion. You may want to provide the key statistics, e.g., t-statistic, z-statistic, p-values,R2and the adjustedR2, etc.