Numerical Python: Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib

© Robert Johansson 2019

Robert JohanssonNumerical Python https://doi.org/10.1007/978-1-4842-4246-9_14

14. Statistical Modeling

Robert Johansson¹ 

(1)

Urayasu-shi, Chiba, Japan

 

In the previous chapter, we covered basic statistical concepts and methods. In this chapter we build on the foundation laid out in the previous chapter and explore statistical modeling, which deals with creating models that attempt to explain data. A model can have one or several parameters, and we can use a fitting procedure to find the values of the parameter that best explains the observed data. Once a model has been fitted to data, it can be used to predict the values of new observations, given the values of the independent variables of the model. We can also perform statistical ...