Python Data Science Handbook

Designed as a textbook for a one or two-term introduction to mathematical statistics for students training to become data scientists, Foundations of Statistics for Data Scientists: With R and Python is an in-depth presentation of the topics in statistical science with which any data scientist should be familiar, including probability distributions, descriptive and inferential statistical methods, and linear modelling. The book assumes knowledge of basic calculus, so the presentation can focus on 'why it works' as well as 'how to do it.' Compared to traditional "mathematical statistics" textbooks, however, the book has less emphasis on probability theory and more emphasis on using software to implement statistical methods and to conduct simulations to illustrate key concepts. All statistical analyses in the book use R software, with an appendix showing the same analyses with Python.The book also introduces modern topics that do not normally appear in mathematical statistics texts but ar

The Routledge Handbook of the Ethics of Immigration is an outstanding reference source to this vitally important topic and will be of great interest to those studying philosophy, politics and related

This handbook provides an overview of current trends and issues in the rapidly developing field of evolutionary economics, an approach which emphasises the levels of the micro (e.g. firms and househol

This Handbook provides a state-of-the-art review of research on environmental policy and governance.

The Routledge Handbook of Energy Law provides a definitive global survey of the discipline of Energy Law, capturing the essential and relevant issues in Energy today. Each chapter is written by a lead

This handbook presents a thorugh introduction to current topics of mathematical research in combinatorial algebraic geometry. Aimed at graduate students researching algebraic combinatorics and Lie theory, and experts in the field and Mathematicians looking for a centralized reference on the geometry and combinatorics of flag varieties.

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This book provides a significant contribution to the increasing conversation concerning the place of big data in education. Offering a multidisciplinary approach with a diversity of perspectives from international scholars and industry experts, chapter authors engage in both research- and industry-informed discussions and analyses on the place of big data in education, particularly as it pertains to large-scale and ongoing assessment practices moving into the digital space. This volume offers an innovative, practical, and international view of the future of current opportunities and challenges in education and the place of assessment in this context.

Statistics Explained, now in its fully revised Fourth Edition, is for students and researchers who wish to understand the statistical analyses used to analyse quantitative (numerical) research data in