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

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

by Robert Johansson
September 2024
Intermediate to advanced content levelIntermediate to advanced
501 pages
17h 6m
English
Apress
Content preview from Numerical Python: Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib
© The Author(s), under exclusive license to APress Media, LLC, part of Springer Nature 2024
R. JohanssonNumerical Pythonhttps://doi.org/10.1007/979-8-8688-0413-7_14

14. Statistical Modeling

Robert Johansson1  
(1)
Urayasu-shi, Chiba, Japan
 

The previous chapter covered basic statistical concepts and methods. This chapter builds on the foundation laid out in the last chapter and explores 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 parameter values so that the model best describes 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 model’s ...

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Publisher Resources

ISBN: 9798868804137Purchase LinkPublisher Website