Mathematical Statistics For Data Science

An introduction to mathematical statistics for data science, covering method of moments, maximum likelihood, and more

Familiarize yourself with fundamental concepts in probability and statistics, data analysis and linear models for Data Science.

Mathematical Statistics for Economics and Business, Second Edition, provides a comprehensive introduction to the principles of mathematical statistics which underpin statistical analyses in the fields of economics, business, and econometrics. The selection of topics in this textbook is designed to provide students with a conceptual foundation that will facilitate a substantial understanding of statistical applications in these subjects. This new edition has been updated throughout and now also includes a downloadable Student Answer Manual containing detailed solutions to half of the over 300 end-of-chapter problems.

Gain control over your data with Math & Stats foundation required for Data Science, Machine Learning & Deep learning

Become a professional Data Scientist and learn how to use NumPy, Pandas, Seaborn, Matplotlib, Machine Learning and more!

Become a professional Data Scientist and learn how to use NumPy, Pandas, Machine Learning and more!

Get your statistics basics right before diving into the world of data science

This book is designed to provide beginning graduate stu­ dents and advanced undergraduates with a rigorous and accessible foundation in the principles of probability and mathematical statistics underlying statis­ tical inference in the fields of business and economics. The book assumes no prior knowledge of probability or statistics and effectively builds the subject "from the ground up." Students who complete their studies of the topics in this text will have acquired the necessary background to achieve a mature and enduring understanding of statistical and econometric methods of inference and will be well equipped to read and comprehend graduate-level economet­ rics texts. Additionally, this text serves as an effective bridge to more advanced study of both mathematical statistics and econometric theory and methods. The book will also be of interest to researchers who desire a decidedly business and economics-oriented treatment of the subject in terms of its topics, depth, breadth, examples, and problems.