Big Data Analytics

Knowing when you're being hoodwinked requires a degree of statistical literacy, but most people don't learn how to interpret statistical claims unless they take a formal course that trains them in the mathematical techniques of statistical analysis. This book won't turn you into a statistician--that would require a much longer and more technical discussion--but it will give you the tools to understand statistical claims and avoid common pitfalls associated with translating statistical information from the language of mathematics to plain English.

In An Introduction to Mathematical Statistics the authors describe key concepts from statistics and give a mathematical basis for important statistical methods. Much attention is paid to the sound application of those methods to data. The three main topics in statistics are estimators, tests, and confidence regions.

A fun introduction to the fundamental principles of statistics, presenting the essential concepts in thirty-four brief, enjoyable stories. Content: Data distributions; Variation of study results: confidence intervals; Hypothesis testing; Regression and decision making.

The subject matter of the book deals with logic, sets, functions and relations, the essential building blocks for higher mathematics. Numerous problems and exercises are chosen and interspersed inside the sections so that the student participates actively in the discussions.Using this book in their studies will lay the foundations which will enable readers to undertake courses in higher mathematics with confidence and due rigour.

This book presents hundreds of practical applications for mathematics--from baseball statistics to the theory of relativity--that can be understood by anyone with a knowledge of high school algebra, geometry and trigonometry.