I'm working on a linear regression analysis using R Studio with an Excel CSV file named 'Student_Performance' located at C:\Users\Documents. The data in Student_Performance.csv includes variables as hours studied, previous scores, extracurricular activities, sleep hours, sample question papers practiced, and performance index.

I need help with the following tasks:

1. Hypotheses and Null Hypothesis: Please provide guidance on formulating my hypotheses and null hypothesis based on the variables in my dataset.
2. Description of the Model: Describe the model I chose for my analysis and explain why I selected it.
3. Dependent and Independent Variables: Provide a description of the main dependent and independent variables in my model, along with summary statistics or graphs.
4. Regression Model Table: Include at least one table from a regression model (it might be logistic regression, if it fits better with my question).
5. Interpretation of the Regression Model: Provide the correct interpretation of the regression model in the context of my hypotheses.
6. R Codes: Please provide R codes for the tasks above, including any concepts from the following lessons I'm using in my paper: Intro to R, Sampling, Simple Linear Regression, Tufte Replication, Multiple Regression, Fish Replication, Other OLS Topics, Interactions, Logit, Heteroskedasticity.
7. Heteroskedasticity and Robust Standard Errors: If applicable, include how to incorporate heteroskedasticity and robust standard errors in my R code.