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

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

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.

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: Chi ]Squared 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 Five ]Hour 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

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Published features on StatisticsViews.com are checked for statistical accuracy by a panel from the European Network for Business and Industrial Statistics (ENBIS)   to whom Wiley and StatisticsViews.com express their gratitude. This panel are: Ron Kenett, David Steinberg, Shirley Coleman, Irena Ograjenšek, Fabrizio Ruggeri, Rainer Göb, Philippe Castagliola, Xavier Tort-Martorell, Bart De Ketelaere, Antonio Pievatolo, Martina Vandebroek, Lance Mitchell, Gilbert Saporta, Helmut Waldl and Stelios Psarakis.