Name: Beyond Basic Statistics: Tips, Tricks, and Techniques Every Data Analyst Should Know (en Inglés)
Price: 76920.00 CLP
Availability: InStock
Author: Jarman, Kristin H.
ISBN: 9781118856116

portada Beyond Basic Statistics: Tips, Tricks, and Techniques Every Data Analyst Should Know (en Inglés)

Beyond Basic Statistics: Tips, Tricks, and Techniques Every Data Analyst Should Know (en Inglés)

Formato

Libro Físico

Autor

Kristin H. Jarman

Editorial

Wiley

Idioma

Inglés

Encuadernación

Tapa Blanda

Dimensiones

23.4 x 15.6 x 1.1 cm

Peso

0.29 kg.

ISBN13

9781118856116

Categorías

Obras de consulta
Probabilidad y estadística
Minería de datos («data mining»)

Beyond Basic Statistics: Tips, Tricks, and Techniques Every Data Analyst Should Know (en Inglés)

Kristin H. Jarman (Autor) · Wiley · Tapa Blanda

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Reseña del libro "Beyond Basic Statistics: Tips, Tricks, and Techniques Every Data Analyst Should Know (en Inglés)"

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.