For this assignment, we will be using the following blood pressure dataset. This dataset contains measurements possibly related to blood pressure from 39 Peruvians who moved from rural high altitude areas to urban lower altitude areas. The dataset contains the following variables:
- Y = Diastolic blood pressure
- \(X_1\) = age
- \(X_2\) = years in urban area
- \(X_3\) = \(X_2/X_1\) = fraction of life in an urban area
- \(X_4\) = weight in kg
- \(X_5\) = height in mm
- \(X_6\) = chin skinfold
- \(X_7\) = forearm skinfold
- \(X_8\) = calf skinfold
- \(X_9\) = resting pulse rate.
Lab 2 - In your software:
- Perform forward stepwise regression using adjusted-\(R^2\).
- Perform backward stepwise selection using BIC.
- Fit this linear regression model using LASSO. Select the tuning parameter using leave on out cross-validation.
Assignment 2 -
- Using the output from the forward stepwise regression to write out the estimated regression equation for the final model. Justify your final model selection.
- For the backward stepwise selection using BIC, write out your final chosen model. Justify your final model choice.