This is the first three chapters of a textbook for data scientists
who want to improve how they work with, analyze, and extract
information from data. The focus of the textbook is how to
appropriately apply statistical methods, both simple and
sophisticated, to 21st century data and problems. This book
contains the first three chapters: Introduction -- Data Science and
Statistics, Descriptive Statistics, and Data Visualization -- as
well as the book front matter. Subsequent chapters will be
published in 3- to 5-chapter sets as they become available. The
textbook is intended for current and future data scientists, and
for anyone interested in deriving information from data. It
requires some mathematical sophistication on the part of the
reader, as well as comfort using computers and statistical
software. Data science is a new field that has arisen to exploit
the proliferation of data in the modern world. Mathematical
statistics dates back to the mid-18th century, where the field
began as the systematic collection of population and economic data
by nations. The modern practice of statistics - which includes the
collection, summarization, and analysis of data - dates to the
early 20th century. Today statistical methods are widely used by
governments, businesses and other organizations, as well as by all
scientific disciplines. It has been said that a data scientist must
have a better grasp of statistics than the average computer
scientist and a better grasp of programming than the average
statistician. This book will give data scientists a firm foundation
in statistics.
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