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Manually predicting house prices

You can manually calculate the predictions from the model coefficients. When making predictions in real life, it is better to use predict(), but doing this manually is helpful to reassure yourself that predictions aren't magic—they are simply arithmetic.

In fact, for a simple linear regression, the predicted value is just the intercept plus the slope times the explanatory variable.

$$response = intercept + slope * explanatory$$

mdl_price_vs_conv and explanatory_data are available, and dplyr is loaded.

Deze oefening maakt deel uit van de cursus

Introduction to Regression in R

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Oefeninstructies

  • Get the coefficients of mdl_price_vs_conv, assigning to coeffs.
  • Get the intercept, which is the first element of coeffs, assigning to intercept.
  • Get the slope, which is the second element of coeffs, assigning to slope.
  • Manually predict price_twd_msq using the intercept, slope, and n_convenience.

Praktische interactieve oefening

Probeer deze oefening eens door deze voorbeeldcode in te vullen.

# Get the coefficients of mdl_price_vs_conv
coeffs <- ___

# Get the intercept
intercept <- ___

# Get the slope
slope <- ___

explanatory_data %>% 
  mutate(
    # Manually calculate the predictions
    price_twd_msq = ___
  )

# Compare to the results from predict()
predict(mdl_price_vs_conv, explanatory_data)
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