Get startedGet started for free

Multivariate linear regression (Part 2)

Now you will make predictions using the blood pressure model bloodpressure_model that you fit in the previous exercise.

You will also compare the predictions to outcomes graphically. ggplot2 has already been loaded. Recall the plot command takes the form:

ggplot(dframe, aes(x = pred, y = outcome)) + 
     geom_point() + 
     geom_abline(color = "blue")

bloodpressure and bloodpressure_model are available for you to use.

This exercise is part of the course

Supervised Learning in R: Regression

View Course

Exercise instructions

  • Use predict() to predict blood pressure in the bloodpressure dataset. Assign the predictions to the column prediction.
  • Graphically compare the predictions to actual blood pressures. Put predictions on the x axis. How close are the results to the line of perfect prediction?

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# bloodpressure is available
summary(bloodpressure)

# bloodpressure_model is available
bloodpressure_model

# Predict blood pressure using bloodpressure_model: prediction
bloodpressure$prediction <- ___

# Plot the results
___ + 
    ___ +
    geom_abline(color = "blue")
Edit and Run Code