- About Dataset
- Description:
- The Student Performance Dataset is a dataset designed to examine the factors influencing academic student performance. The dataset consists of 10,000 student records, with each record containing information about various predictors and a performance index.
- Variables:
- Hours Studied: The total number of hours spent studying by each student.
- Previous Scores: The scores obtained by students in previous tests.
- Extracurricular Activities: Whether the student participates in extracurricular activities (Yes or No).
- Sleep Hours: The average number of hours of sleep the student had per day.
- Sample Question Papers Practiced: The number of sample question papers the student practiced.
- Performance Index: A measure of the overall performance of each student. The performance index represents the student's academic performance and has been rounded to the nearest integer. The index ranges from 10 to 100, with higher values indicating better performance.
- Questions :
- 1. Identify the dependent variable and the independent variables in the dataset given for the regression analysis. -- 5
- 2. Find the relation of the dependent variable with each independent variable (Hint : Correlation). Explore more about correlation -- 10
- 3. Create a basic linear regression model and fit it using python. -- 20
- 4. From the above model created , find the coefficients and intercept of the variables created. -- 10
- 5. Understand about the difference between the interpretation of the simple linear regression and correlation. Explain with example from the dataset. -- 10
- 6. Calculate the predicted values of your dependent variable and observe how good you are getting the results (Hint: Closer the predicted and actual values better the model).
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