In this step by step guide, we will walk you through the python stats models package and along with that we also covering some glimpses of this packages built-in functions. We take a theoretical plus practical approach to have a better hands-on experience. Let’s Dive In !
Statsmodels
The Python module statsmodels offers numerous statistical
functions to create statistical models and assess their
performances. This module also provides a range of statistical
tests to explore a given dataset.
In statsmodels, we can specify the details of the statistical model using formulas or array objects. This is an example to generate a regression model using ordinary least squares (OLS).
The output of the code describes a number of statistics related to the regression model. The reader may not be familiar with a lot of terms in the output. However, at this stage it is not very important to understand the minute details of the statistical models. We shall get back to these concepts in the later modules. However it is important to realize the powerful features of the statsmodels library.
Conclusion
Finally, we covering the python statsmodels library that is basically so important when we deal with statistics and in other words we deal with large volume of data. If you whenever work with time series analysis, than you point it, because this package is used specially for weather forecasting that provides predictional results.
