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

Book Description

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.

    Table of Contents

    1. COVER
    2. TITLE PAGE
    3. PREFACE
    4. 1 INTRODUCTION: IT SEEMED LIKE THE RIGHT THING TO DO AT THE TIME
      1. WHEN GOOD STATISTICS GO BAD: COMMON MISTAKES AND THE IMPACT THEY HAVE
      2. STATISTICS 101: CONCEPTS YOU SHOULD KNOW BEFORE READING THIS BOOK
      3. TIPS, TRICKS, AND TECHNIQUES: A ROADMAP OF WHAT FOLLOWS
      4. BIBLIOGRAPHY
    5. 2 THE TYPE A DIET: SAMPLING STRATEGIES TO ELIMINATE CONFOUNDING AND REDUCE YOUR WAISTLINE
      1. THE BASICS OF PLANNING A STUDY
      2. MY STATISTICAL ANALYSIS IS BRILLIANT. WHY ARE MY CONCLUSIONS SO WRONG?
      3. REPLICATION, RANDOMIZATION, AND BLOCKING: THE BUILDING BLOCKS A GOOD STUDY
      4. EXPLORATORY RESEARCH: GETTING YOUR STUDIES INTO FOCUS
      5. DESCRIPTIVE AND EXPLANATORY RESEARCH: ANSWERING THE TARGETED QUESTIONS
      6. SO MANY STRATEGIES, SO LITTLE TIME
      7. BIBLIOGRAPHY
    6. 3 CONSERVATIVES, LIBERALS, AND OTHER POLITICAL PAWNS: HOW TO GAIN POWER AND INFLUENCE WITH SAMPLE SIZE CALCULATIONS
      1. STEP 1. KEEP YOUR FINGER ON THE PULSE OF THE POPULACE
      2. STEP 2. AVOID AMBIGUOUS RESULTS AND OTHER POLITICAL POTHOLES
      3. STEP 3. LET SAMPLE-SIZE CALCULATIONS BE YOUR RIGHT-HAND MAN
      4. STEP 4. KEEP YOUR FRIENDS CLOSE AND YOUR ENEMIES CLOSER
      5. BIBLIOGRAPHY
    7. 4 BUNCO, BRICKS, AND MARKED CARDS: CHI-SQUARED TESTS AND HOW TO BEAT A CHEATER
      1. WHAT HAPPENS IN VEGAS … HOW STATISTICIANS REMAIN DISCRETE
      2. CONTINGENCY TABLES, CHI-SQUARED TESTS, AND OTHER WINNING STRATEGIES FOR DISCRETE DATA ANALYSIS
      3. HOW TO BEAT A CHEATER
      4. BIBLIOGRAPHY
    8. 5 WHY IT PAYS TO BE A STABLE MASTER: SUMO WRESTLERS AND OTHER ROBUST STATISTICS
      1. DESCRIPTIVE STATISTICS: A REVIEW FOR THE <i xmlns="http://www.w3.org/1999/xhtml" xmlns:epub="http://www.idpf.org/2007/ops" xmlns:m="http://www.w3.org/1998/Math/MathML" xmlns:svg="http://www.w3.org/2000/svg" xmlns:ibooks="http://vocabulary.itunes.apple.com/rdf/ibooks/vocabulary-extensions-1.0">JONOKUCHI</i>
      2. THE JAPANESE SUMO INVASION: WHY IT PAYS TO BE ROBUST
      3. WHEN ROBUST DOES IT BETTER
      4. HARVESTING THE AMERICAN DREAM
      5. BIBLIOGRAPHY
    9. 6 FIVE-HOUR MARRIAGES: CONTINUOUS DISTRIBUTIONS, TESTS FOR NORMALITY, AND JUICY HOLLYWOOD SCANDALS
      1. THE NORMAL DISTRIBUTION: THE MOST ORDINARY OF ALL PROBABILITY DISTRIBUTIONS
      2. NORMALITY TESTS EVERY DATA ANALYST SHOULD KNOW
      3. DATA TRANSFORMATIONS AND OTHER STRATEGIES FOR COPING WITH NON-NORMAL DATA
      4. THERE’S NORMAL, AND THEN THERE’S HOLLYWOOD NORMAL
      5. BIBLIOGRAPHY
    10. 7 BELIEVE IT OR DON’T: USING OUTLIER DETECTION TO FIND THE WEIRDEST OF THE WEIRD
      1. THE WORLD OF THE WEIRD
      2. OUTLIER AND ANOMALY DETECTION: KNOWING AN ODDITY WHEN YOU SEE ONE
      3. SO, YOU’VE FOUND AN ODDITY. WHAT NOW?
      4. THE WEIRDEST OF THE WEIRD
      5. BIBLIOGRAPHY
    11. 8 THE BATTLE OF THE MOVIE MONSTERS, ROUND TWO: RAMPING UP HYPOTHESIS TESTS WITH NONPARAMETRIC STATISTICS
      1. THE PARAMETRIC HYPOTHESIS TEST: A CONVENTIONAL WEAPON FOR CONVENTIONAL BATTLES
      2. NONPARAMETRIC TESTS: WHEN YOU NEED TO EXERCISE THE NUCLEAR OPTION
      3. WHEN TO USE THE NUCLEAR OPTION
      4. GODZILLA VERSUS KING KONG, ROUND TWO
      5. BIBLIOGRAPHY
    12. 9 MODELS, MURPHY’S LAW, AND PUBLIC HUMILIATION: REGRESSION RULES TO LIVE BY
      1. MURPHY’S LAW AND SIMPLE LINEAR REGRESSION: A REVIEW OF TWO CLASSICS
      2. BEYOND SIMPLE LINEAR REGRESSION: COMMON MODELS FOR COMMON SITUATIONS
      3. MISTAKES AND OTHER EMBARRASSMENTS TO AVOID
      4. WHAT COULD GO WRONG, DID GO WRONG
      5. WHAT I DID
      6. BIBLIOGRAPHY
    13. APPENDIX A: CRITICAL VALUES FOR THE STANDARD NORMAL DISTRIBUTION
    14. APPENDIX B: CRITICAL VALUES FOR THE <i xmlns="http://www.w3.org/1999/xhtml" xmlns:epub="http://www.idpf.org/2007/ops" xmlns:m="http://www.w3.org/1998/Math/MathML" xmlns:svg="http://www.w3.org/2000/svg" xmlns:ibooks="http://vocabulary.itunes.apple.com/rdf/ibooks/vocabulary-extensions-1.0">T</i>-DISTRIBUTION-DISTRIBUTION
    15. APPENDIX C: CRITICAL VALUES FOR THE CHI-SQUARED DISTRIBUTION
    16. APPENDIX D: CRITICAL VALUES FOR GRUBBS’ TEST
    17. APPENDIX E: CRITICAL VALUES FOR WILCOXSON SIGNED RANK TEST: SMALL SAMPLE SIZES
    18. GLOSSARY
    19. INDEX
    20. END USER LICENSE AGREEMENT