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
Exercise instructions
- Use
predict()
to predict blood pressure in thebloodpressure
dataset. Assign the predictions to the columnprediction
. - 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")