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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.

My online courses are closed for enrollment.
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