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Modern Statistics : A Computer-Based Approach with Python by Ron S. Kenett; Shelemyahu Zacks; Peter Gedeck is a nonfiction available to read on EtoBox.

What is Modern Statistics : A Computer-Based Approach with Python about?

This innovative textbook presents material for a course on modern statistics that incorporates Python as a pedagogical and practical resource. Drawing on many years of teaching and conducting research in various applied and industrial settings, the authors have carefully tailored the text to provide an ideal balance of theory and practical applications. Numerous examples and case studies are incorporated throughout, and comprehensive Python applications are illustrated in detail. A custom Python package is available for download, allowing students to reproduce these examples and explore others. The first chapters of the text focus on analyzing variability, probability models, and distribution functions. Next, the authors introduce statistical inference and bootstrapping, and variability in several dimensions and regression models. The text then goes on to cover sampling for estimation of finite population quantities and time series analysis and prediction, concluding with two chapters on modern data analytic methods. Each chapter includes exercises, data sets, and applications to supplement learning. Modern Statistics: A Computer-Based Approach with Python is intended for a one- or

Who reads Modern Statistics : A Computer-Based Approach with Python?

Author

Ron S. Kenett; Shelemyahu Zacks; Peter Gedeck

Publisher

Springer International Publishing : Imprint: Birkhäuser

Published

2022

Language

EN

ISBN

9783031075650

Category

nonfiction

Subjects

Mathematics, Engineering, Computer Science