This is a dataset to track performance of students in their exams. The dataset was created with an intention to tract the effect of external factors on performance of students in their exams. The factors taken into account or the features in the dataset are:- 1. Gender - Male/Female 2. Race/Ethnicity - Customized classification into ‘group A’, ‘group B’, ‘group C’, ‘group D’, ‘group E’. 3. Parental education level - This is the level of education attained by the parents of students. It's classified as an ‘associate's degree’, ‘bachelor’s degree’, ‘high school’, ‘master’s degree’, ‘some college’ or ‘ some high school’. 4. Lunch - This defines the type of lunch students get according to the school standards. Its classified as ‘standard’ or ‘free/reduced’. This is a binary feature. 5. Test preparation - As the name suggests, this attribute captures whether the students have completed their test preparation or not. It is a binary feature with classes as ‘completed’ and ‘none’. 6. Math score - This is a numerical feature capturing the scores of students in mathematics. 7. Reading score - This is also a numerical feature capturing the scores of students in reading. 8. Writing score - This is another numerical feature which captures the scores of students in writing.