Linear Regression: Residual Standard Error in Python Videos

Last Update: March 22, 2022

My online video tutorials are hosted at YouTube channel.

For learning this concept, you can view my online video tutorials: Linear Regression: Residual Standard Error in Python (Spyder) and Linear Regression: Residual Standard Error in Python (Jupyter).

Videos Code

1. Packages

import numpy as np
import statsmodels.api as sm
import statsmodels.formula.api as smf

2. Data

houseprices_object = sm.datasets.get_rdataset(dataname="HousePrices",
                                              package="AER", cache=True)
houseprices = houseprices_object.data
print(houseprices.iloc[:, 0:3].head())
print(houseprices_object.__doc__)

3. Model

mlr = smf.ols(formula="price ~ lotsize + bedrooms", 
              data=houseprices).fit()

4. Results

print(np.sqrt(mlr.mse_resid))
print(np.sqrt(sum(mlr.resid ** 2) / mlr.df_resid))

Courses

My online courses are hosted at Teachable website.

For more details on this concept, you can view my Linear Regression in Python Course.