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Multivariate linear regression (Part 1)

In this exercise, you will work with the blood pressure dataset (Source), and model blood_pressure as a function of weight and age.

The data frame bloodpressure has been pre-loaded for you.

This exercise is part of the course

Supervised Learning in R: Regression

View Course

Exercise instructions

  • Define a formula that expresses blood_pressure explicitly as a function of age and weight. Assign the formula to the variable fmla and print it.
  • Use fmla to fit a linear model to predict blood_pressure from age and weight in the dataset bloodpressure. Call the model bloodpressure_model.
  • Print the model and call summary() on it. Does blood pressure increase or decrease with age? With weight?

Hands-on interactive exercise

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

# bloodpressure is available
summary(bloodpressure)

# Create the formula and print it
fmla <- ___
___

# Fit the model: bloodpressure_model
bloodpressure_model <- ___

# Print bloodpressure_model and call summary() 
___
___
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