Features basic statistical concepts as a tool for thinking critically, wading through large quantities of information, and answering practical, everyday questions
Written in an engaging and inviting manner, Beyond Basic Statistics: Tips, Tricks, and Techniques Every Data Analyst Should Know presents the more subjective side of statistics—the art of data analytics. Each chapter explores a different question using fun, common sense examples that illustrate the concepts, methods, and applications of statistical techniques.
Without going into the specifics of theorems, propositions, or formulas, the book effectively demonstrates statistics as a useful problem-solving tool. In addition, the author demonstrates how statistics is a tool for thinking critically, wading through large volumes of information, and answering life’s important questions.
Beyond Basic Statistics: Tips, Tricks, and Techniques Every Data Analyst Should Know also features:
- Plentiful examples throughout aimed to strengthen readers’ understanding of the statistical concepts and methods
- A step-by-step approach to elementary statistical topics such as sampling, hypothesis tests, outlier detection, normality tests, robust statistics, and multiple regression
- A case study in each chapter that illustrates the use of the presented techniques
- Highlights of well-known shortcomings that can lead to false conclusions
- An introduction to advanced techniques such as validation and bootstrapping
Featuring examples that are engaging and non-application specific, the book appeals to a broad audience of students and professionals alike, specifically students of undergraduate statistics, managers, medical professionals, and anyone who has to make decisions based on raw data or compiled results.
Keywords: statistics; data analysis; probability; applied statistics; critical thinking; big data; sampling; hypothesis tests; robust statistics; ANOVA comparisons; multiple regression; statisticians; analytics; nonparametric statistics, General & Introductory Statistics, Applied Probability & Statistics, General & Introductory Statistics, Applied Probability & Statistics