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Graphically evaluate the unemployment model

In this exercise, you will graphically evaluate the unemployment model, unemployment_model, that you fit to the unemployment data in the previous chapter. Recall that the model predicts female_unemployment from male_unemployment.

You will plot the model's predictions against the actual female_unemployment; recall the command is of the form

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

Then you will calculate the residuals:

residuals <- actual outcome - predicted outcome

and plot predictions against residuals. The residual graph will take a slightly different form: you compare the residuals to the horizontal line \(y=0\) (using geom_hline()) rather than to the line \(x=y\). The command will be provided.

The data frame unemployment and model unemployment_model have been pre-loaded.

This exercise is part of the course

Supervised Learning in R: Regression

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Hands-on interactive exercise

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

# unemployment and unemployment_model are available
summary(unemployment)
summary(unemployment_model)

# Make predictions from the model
unemployment$predictions <- ___

# Fill in the blanks to plot predictions (on x-axis) versus the female_unemployment rates
___(___, aes(x = ___, y = ___)) + 
  geom_point() + 
  geom_abline()
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