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Making predictions using size and waterfront

Using your model for log10_price as a function of log10_size and the binary variable waterfront, let's make some predictions! Say you have the two following "new" houses, what would you predict their prices to be in dollars?

  • House A: log10_size = 2.9 that has a view of the waterfront
  • House B: log10_size = 3.1 that does not have a view of the waterfront

We make the corresponding visual predictions below:

This exercise is part of the course

Modeling with Data in the Tidyverse

View Course

Exercise instructions

After running the code on line 2 to get the regression table based on model_price_4, compute the predicted prices for both houses. First you'll use an equation based on values in this regression table to get a predicted value in log10 dollars, then raise 10 to this predicted value to get a predicted value in dollars.

Hands-on interactive exercise

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

# Get regression table
get_regression_table(model_price_4)

# Prediction for House A
10^(___)

# Prediction for House B
10^(___)
Edit and Run Code