1) Consider 70% for training dataset and 30% for validation dataset and fit a regression model using training dataset and apply all the concepts which were covered

2) Once the final model is done.Find the predicted values for validation dataset using the model obtained by training dataset.Compute R square and Root Mean Square and compare these values with R square and Residual Standard error obtained by the training model.

a) Checking whether linear regression modeling is appropriate for a problem at hand,

b) Developing a linear regression model when appropriate and

c) Validating a developed model.