Comparing coefficients of determination
Recall that the coefficient of determination is a measure of how well the linear regression line fits the observed values. An important motivation for including several explanatory variables in a linear regression is that you can improve the fit compared to considering only a single explanatory variable.
Here you'll compare the coefficient of determination for the three Taiwan house price models, to see which gives the best result.
mdl_price_vs_conv, mdl_price_vs_age, and mdl_price_vs_both are available as fitted models.
Deze oefening maakt deel uit van de cursus
Intermediate Regression with statsmodels in Python
Praktische interactieve oefening
Probeer deze oefening eens door deze voorbeeldcode in te vullen.
# Print the coeffs of determination for mdl_price_vs_conv
print("rsquared_conv: ", ____)
print("rsquared_adj_conv: ", ____)
# Print the coeffs of determination for mdl_price_vs_age
print("rsquared_age: ", ____)
print("rsquared_adj_age: ", ____)
# Print the coeffs of determination for mdl_price_vs_both
print("rsquared_both: ", ____)
print("rsquared_adj_both: ", ____)