Beyond Basic Statistics: Tips, Tricks, and Techniques Every Data Analyst Should

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Características del artículo

Estado
Como nuevo: Libro en perfecto estado y poco leído. La tapa no tiene desperfectos y si procede, con ...
Book Title
Beyond Basic Statistics: Tips, Tricks, and Techniques Every Data
ISBN
9781118856116
Categoría

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Product Identifiers

Publisher
Wiley & Sons, Incorporated, John
ISBN-10
1118856112
ISBN-13
9781118856116
eBay Product ID (ePID)
208636442

Product Key Features

Number of Pages
208 Pages
Publication Name
Beyond Basic Statistics : Tips, Tricks, and Techniques Every Data Analyst Should Know
Language
English
Subject
Probability & Statistics / General, Reference, Databases / Data Mining
Publication Year
2015
Type
Textbook
Subject Area
Mathematics, Computers
Author
Kristin H. Jarman
Format
Trade Paperback

Dimensions

Item Height
0.4 in
Item Weight
14.1 Oz
Item Length
9.3 in
Item Width
6.1 in

Additional Product Features

Intended Audience
Scholarly & Professional
LCCN
2014-047952
Dewey Edition
23
Reviews
"This is a consistently entertaining and instructive book. The stories are interspersed with serious background material, and the combination works very well. This would be entirely suitable as supplementary reading for a statistics course or for an independent reading project." ( MAA Reviews , 20 September 2015)
Illustrated
Yes
Dewey Decimal
001.4/22
Table Of Content
Preface ix 1 Introduction: It Seemed like the Right Thing to Do at the Time 1 2 The Type A Diet: Sampling Strategies to Eliminate Confounding and Reduce Your Waistline 9 3 Conservatives, Liberals, and Other Political Pawns: How to Gain Power and Influence with Sample Size Calculations 31 4 Bunco, Bricks, and Marked Cards: ChiSquared Tests and How to Beat a Cheater 47 5 Why it Pays to be a Stable Master: Sumo Wrestlers and Other Robust Statistics 69 6 FiveHour Marriages: Continuous Distributions, Tests for Normality, and Juicy Hollywood Scandals 91 7 Believe It or Don't: Using Outlier Detection to Find the Weirdest of the Weird 109 8 The Battle of the Movie Monsters, Round Two: Ramping up Hypothesis Tests with Nonparametric Statistics 123 9 Models, Murphy's Law, and Public Humiliation: Regression Rules to Live By 139 Appendix A Critical Values for the Standard Normal Distribution 163 Appendix B Critical Values for the T-Distribution 165 Appendix C Critical Values for the Chi-Squared Distribution 167 Appendix D Critical Values for Grubbs' Test 169 Appendix E Critical Values for Wilcoxson Signed Rank Test: Small Sample Sizes 171 Glossary 173 Index 185
Synopsis
This book focuses on the more subjective side of statistics - the art of data analysis.   Using a handful of fun examples, each chapter asks a single question, illustrating the different ways that questions can be answered with techniques taught in any introductory statistics course., 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., 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 lifes 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 illustrating the use of these 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, this 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.
LC Classification Number
QA276.J37 2015

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