Need help please!

We will be using the College dataset in the ISLR package in R. 1} First, we will t a multiple linear regression model to the data to make predictions about a college's out-of-state tuition from all other variables in College. a. (5 points} Use mathematical notation to state the null hypothesis for your multiple linear regression model, ensuring to indicate the number of features in your model. b. (5 points) Provide the test statistic and associated p value for your hypothesis test from 1a. c. (5 points) Draw an appropriate conclusion based on the results of your hypothesis test. d. (5 points} Briefly explain what this conclusion means about the linear relationship between a college's out-of-state tuition and the features in your model. e. (5 points) According to your model, which features are linearly related to a college's out-of-state tuition? f. (5 points) Which of the features listed in 1e is most strongly related to a college's out-ofstate tuition? How do you know? 3. (5 points) What does the feature in if represent? Hint: Think about the type of variable in the Col lege dataset. h. (5 points) Taking into consideration your answer to lg, briefly explain the relationship between the feature in if and a college's out-ofstate tuition. Be specic about how much the average tuition will change with changes to the value of this feature. (5 points) Provide the values of the two goodness-of-fit statistics computed for this model. j. (5 points) Compare the statistics from lg to those obtained for the simple linear regression model from Homework 2. Based on your comparisons, which model has a better fit