Amazon cover image
Image from Amazon.com

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

By: Publisher: New York : John Wiley & Sons, Incorporated, 2015Copyright date: ©2015Edition: 1st edDescription: 1 online resource (203 pages)Content type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781118856123
Subject(s): Genre/Form: Additional physical formats: Print version:: Beyond Basic Statistics : Tips, Tricks, and Techniques Every Data Analyst Should KnowDDC classification:
  • 001.4/22
LOC classification:
  • QA276 .J37 2015
Online resources:
Contents:
Intro -- Title Page -- Copyright Page -- Contents -- Preface -- Chapter 1 Introduction: It Seemed Like the Right Thing To Do at the Time -- WHEN GOOD STATISTICS GO BAD: COMMON MISTAKES AND THE IMPACT THEY HAVE -- STATISTICS 101: CONCEPTS YOU SHOULD KNOW BEFORE READING THIS BOOK -- Probability Theory -- Statistics -- TIPS, TRICKS, AND TECHNIQUES: A ROADMAP OF WHAT FOLLOWS -- BIBLIOGRAPHY -- Chapter 2 The Type A Diet: Sampling Strategies to Eliminate Confounding and Reduce Your Waistline -- THE BASICS OF PLANNING A STUDY -- MY STATISTICAL ANALYSIS IS BRILLIANT. WHY ARE MY CONCLUSIONS SO WRONG? -- Answering the Wrong Question -- Putting Too Much Confidence in Convenience Data -- Confusing Association and Causation -- REPLICATION, RANDOMIZATION, AND BLOCKING: THE BUILDING BLOCKS A GOOD STUDY -- EXPLORATORY RESEARCH: GETTING YOUR STUDIES INTO FOCUS -- DESCRIPTIVE AND EXPLANATORY RESEARCH: ANSWERING THE TARGETED QUESTIONS -- Controlled Experiments: The Art of Manipulation -- Observational Studies: Scientifically Approved Voyeurism -- SO MANY STRATEGIES, SO LITTLE TIME -- BIBLIOGRAPHY -- Chapter 3 Conservatives, Liberals, and Other Political Pawns: How to Gain Power and Influence with Sample Size Calculations -- STEP 1. KEEP YOUR FINGER ON THE PULSE OF THE POPULACE -- STEP 2. AVOID AMBIGUOUS RESULTS AND OTHER POLITICAL POTHOLES -- Identify the Data Analysis Technique You Will Be Performing -- Know the Difference Between Practical Significance and Statistical Significance -- Note Your Practical Limitations -- STEP 3. LET SAMPLE-SIZE CALCULATIONS BE YOUR RIGHT-HAND MAN -- Population Means and Probabilities: Sample-Size Calculations for a Confidence Interval -- Power and Sample-Size Calculations for Hypothesis Tests -- STEP 4. KEEP YOUR FRIENDS CLOSE AND YOUR ENEMIES CLOSER -- BIBLIOGRAPHY.
Chapter 4 Bunco, Bricks, and Marked Cards: Chi-Squared Tests and How to Beat a Cheater -- WHAT HAPPENS IN VEGAS … HOW STATISTICIANS REMAIN DISCRETE -- CONTINGENCY TABLES, CHI-SQUARED TESTS, AND OTHER WINNING STRATEGIES FOR DISCRETE DATA ANALYSIS -- Turning Lemons into Gold Bars: How to Convert Qualitative Data into Quantitative Random Variables -- Plots and Tables: The Poor Man's Statistical Analysis -- Contingency Tables: How to Break Down a Frequency Distribution and Expose Your Variables -- The Chi-Squared Test: An All-You-Can-Eat Buffet for Discrete Data Analysis -- HOW TO BEAT A CHEATER -- BIBLIOGRAPHY -- Chapter 5 WHY IT PAYS TO BE A STABLE MASTER: SUMO WRESTLERS AND OTHER ROBUST STATISTICS -- DESCRIPTIVE STATISTICS: A REVIEW FOR THE JONOKUCHI -- Three Things You Should Know About the Sample Mean -- Three Things You Should Know about the Standard Deviation -- THE JAPANESE SUMO INVASION: WHY IT PAYS TO BE ROBUST -- Summarizing a Sample with Percentiles -- Robust Center Location -- Robust and Resistant Variation -- Robust Confidence Intervals -- WHEN ROBUST DOES IT BETTER -- HARVESTING THE AMERICAN DREAM -- BIBLIOGRAPHY -- Chapter 6 Five-Hour Marriages: Continuous Distributions, Tests for Normality, and Juicy Hollywood Scandals -- THE NORMAL DISTRIBUTION: THE MOST ORDINARY OF ALL PROBABILITY DISTRIBUTIONS -- NORMALITY TESTS EVERY DATA ANALYST SHOULD KNOW -- Q-Q Plots: A Picture Is Worth a Thousand Words -- Hypothesis Tests for Normality -- DATA TRANSFORMATIONS AND OTHER STRATEGIES FOR COPING WITH NON‐NORMAL DATA -- THERE'S NORMAL, AND THEN THERE'S HOLLYWOOD NORMAL -- BIBLIOGRAPHY -- Chapter 7 Believe It or Don't: Using Outlier Detection to Find the Weirdest of the Weird -- THE WORLD OF THE WEIRD -- OUTLIER AND ANOMALY DETECTION: KNOWING AN ODDITY WHEN YOU SEE ONE -- z-scores, Not Just for t-Tests Anymore.
The Interquartile Range Test for Robust Outlier Detection -- Grubbs' Test: An Exact Test for Finding Outliers -- SO, YOU'VE FOUND AN ODDITY. WHAT NOW? -- THE WEIRDEST OF THE WEIRD -- BIBLIOGRAPHY -- Chapter 8 The Battle of the Movie Monsters, Round Two: Ramping Up Hypothesis Tests with Nonparametric Statistics -- THE PARAMETRIC HYPOTHESIS TEST: A CONVENTIONAL WEAPON FOR CONVENTIONAL BATTLES -- NONPARAMETRIC TESTS: WHEN YOU NEED TO EXERCISE THE NUCLEAR OPTION -- The Sign Test -- The Sign Test for Paired Data -- Wilcoxon Signed Rank Test -- Kruskal-Wallis -- WHEN TO USE THE NUCLEAR OPTION -- GODZILLA VERSUS KING KONG, ROUND TWO -- BIBLIOGRAPHY -- Chapter 9 Models, Murphy's Law, and Public Humiliation: Regression Rules to Live By -- MURPHY'S LAW AND SIMPLE LINEAR REGRESSION: A REVIEW OF TWO CLASSICS -- Basic Regression Diagnostics -- BEYOND SIMPLE LINEAR REGRESSION: COMMON MODELS FOR COMMON SITUATIONS -- Multiple Linear Regression -- Polynomial Regression -- Stepwise Regression -- Multivariate Regression -- Nonlinear Regression -- MISTAKES AND OTHER EMBARRASSMENTS TO AVOID -- WHAT COULD GO WRONG, DID GO WRONG -- WHAT I DID -- What I Should've Done -- BIBLIOGRAPHY -- Appendix A: Critical Values for the Standard Normal Distribution -- Appendix B: Critical Values for the T-Distribution -- Appendix C: Critical Values for the Chi-Squared Distribution -- Appendix D: Critical Values for Grubbs' Test -- Appendix E: Critical Values for Wilcoxson Signed Rank Test: Small Sample Sizes -- Glossary -- Index -- EULA.
Summary: 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.
Holdings
Item type Current library Call number Status Date due Barcode Item holds
Ebrary Ebrary Afghanistan Available EBKAF-N0001507
Ebrary Ebrary Algeria Available
Ebrary Ebrary Cyprus Available
Ebrary Ebrary Egypt Available
Ebrary Ebrary Libya Available
Ebrary Ebrary Morocco Available
Ebrary Ebrary Nepal Available EBKNP-N0001507
Ebrary Ebrary Sudan Available
Ebrary Ebrary Tunisia Available
Total holds: 0

Intro -- Title Page -- Copyright Page -- Contents -- Preface -- Chapter 1 Introduction: It Seemed Like the Right Thing To Do at the Time -- WHEN GOOD STATISTICS GO BAD: COMMON MISTAKES AND THE IMPACT THEY HAVE -- STATISTICS 101: CONCEPTS YOU SHOULD KNOW BEFORE READING THIS BOOK -- Probability Theory -- Statistics -- TIPS, TRICKS, AND TECHNIQUES: A ROADMAP OF WHAT FOLLOWS -- BIBLIOGRAPHY -- Chapter 2 The Type A Diet: Sampling Strategies to Eliminate Confounding and Reduce Your Waistline -- THE BASICS OF PLANNING A STUDY -- MY STATISTICAL ANALYSIS IS BRILLIANT. WHY ARE MY CONCLUSIONS SO WRONG? -- Answering the Wrong Question -- Putting Too Much Confidence in Convenience Data -- Confusing Association and Causation -- REPLICATION, RANDOMIZATION, AND BLOCKING: THE BUILDING BLOCKS A GOOD STUDY -- EXPLORATORY RESEARCH: GETTING YOUR STUDIES INTO FOCUS -- DESCRIPTIVE AND EXPLANATORY RESEARCH: ANSWERING THE TARGETED QUESTIONS -- Controlled Experiments: The Art of Manipulation -- Observational Studies: Scientifically Approved Voyeurism -- SO MANY STRATEGIES, SO LITTLE TIME -- BIBLIOGRAPHY -- Chapter 3 Conservatives, Liberals, and Other Political Pawns: How to Gain Power and Influence with Sample Size Calculations -- STEP 1. KEEP YOUR FINGER ON THE PULSE OF THE POPULACE -- STEP 2. AVOID AMBIGUOUS RESULTS AND OTHER POLITICAL POTHOLES -- Identify the Data Analysis Technique You Will Be Performing -- Know the Difference Between Practical Significance and Statistical Significance -- Note Your Practical Limitations -- STEP 3. LET SAMPLE-SIZE CALCULATIONS BE YOUR RIGHT-HAND MAN -- Population Means and Probabilities: Sample-Size Calculations for a Confidence Interval -- Power and Sample-Size Calculations for Hypothesis Tests -- STEP 4. KEEP YOUR FRIENDS CLOSE AND YOUR ENEMIES CLOSER -- BIBLIOGRAPHY.

Chapter 4 Bunco, Bricks, and Marked Cards: Chi-Squared Tests and How to Beat a Cheater -- WHAT HAPPENS IN VEGAS … HOW STATISTICIANS REMAIN DISCRETE -- CONTINGENCY TABLES, CHI-SQUARED TESTS, AND OTHER WINNING STRATEGIES FOR DISCRETE DATA ANALYSIS -- Turning Lemons into Gold Bars: How to Convert Qualitative Data into Quantitative Random Variables -- Plots and Tables: The Poor Man's Statistical Analysis -- Contingency Tables: How to Break Down a Frequency Distribution and Expose Your Variables -- The Chi-Squared Test: An All-You-Can-Eat Buffet for Discrete Data Analysis -- HOW TO BEAT A CHEATER -- BIBLIOGRAPHY -- Chapter 5 WHY IT PAYS TO BE A STABLE MASTER: SUMO WRESTLERS AND OTHER ROBUST STATISTICS -- DESCRIPTIVE STATISTICS: A REVIEW FOR THE JONOKUCHI -- Three Things You Should Know About the Sample Mean -- Three Things You Should Know about the Standard Deviation -- THE JAPANESE SUMO INVASION: WHY IT PAYS TO BE ROBUST -- Summarizing a Sample with Percentiles -- Robust Center Location -- Robust and Resistant Variation -- Robust Confidence Intervals -- WHEN ROBUST DOES IT BETTER -- HARVESTING THE AMERICAN DREAM -- BIBLIOGRAPHY -- Chapter 6 Five-Hour Marriages: Continuous Distributions, Tests for Normality, and Juicy Hollywood Scandals -- THE NORMAL DISTRIBUTION: THE MOST ORDINARY OF ALL PROBABILITY DISTRIBUTIONS -- NORMALITY TESTS EVERY DATA ANALYST SHOULD KNOW -- Q-Q Plots: A Picture Is Worth a Thousand Words -- Hypothesis Tests for Normality -- DATA TRANSFORMATIONS AND OTHER STRATEGIES FOR COPING WITH NON‐NORMAL DATA -- THERE'S NORMAL, AND THEN THERE'S HOLLYWOOD NORMAL -- BIBLIOGRAPHY -- Chapter 7 Believe It or Don't: Using Outlier Detection to Find the Weirdest of the Weird -- THE WORLD OF THE WEIRD -- OUTLIER AND ANOMALY DETECTION: KNOWING AN ODDITY WHEN YOU SEE ONE -- z-scores, Not Just for t-Tests Anymore.

The Interquartile Range Test for Robust Outlier Detection -- Grubbs' Test: An Exact Test for Finding Outliers -- SO, YOU'VE FOUND AN ODDITY. WHAT NOW? -- THE WEIRDEST OF THE WEIRD -- BIBLIOGRAPHY -- Chapter 8 The Battle of the Movie Monsters, Round Two: Ramping Up Hypothesis Tests with Nonparametric Statistics -- THE PARAMETRIC HYPOTHESIS TEST: A CONVENTIONAL WEAPON FOR CONVENTIONAL BATTLES -- NONPARAMETRIC TESTS: WHEN YOU NEED TO EXERCISE THE NUCLEAR OPTION -- The Sign Test -- The Sign Test for Paired Data -- Wilcoxon Signed Rank Test -- Kruskal-Wallis -- WHEN TO USE THE NUCLEAR OPTION -- GODZILLA VERSUS KING KONG, ROUND TWO -- BIBLIOGRAPHY -- Chapter 9 Models, Murphy's Law, and Public Humiliation: Regression Rules to Live By -- MURPHY'S LAW AND SIMPLE LINEAR REGRESSION: A REVIEW OF TWO CLASSICS -- Basic Regression Diagnostics -- BEYOND SIMPLE LINEAR REGRESSION: COMMON MODELS FOR COMMON SITUATIONS -- Multiple Linear Regression -- Polynomial Regression -- Stepwise Regression -- Multivariate Regression -- Nonlinear Regression -- MISTAKES AND OTHER EMBARRASSMENTS TO AVOID -- WHAT COULD GO WRONG, DID GO WRONG -- WHAT I DID -- What I Should've Done -- BIBLIOGRAPHY -- Appendix A: Critical Values for the Standard Normal Distribution -- Appendix B: Critical Values for the T-Distribution -- Appendix C: Critical Values for the Chi-Squared Distribution -- Appendix D: Critical Values for Grubbs' Test -- Appendix E: Critical Values for Wilcoxson Signed Rank Test: Small Sample Sizes -- Glossary -- Index -- EULA.

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.

Description based on publisher supplied metadata and other sources.

Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2019. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.

There are no comments on this title.

to post a comment.