Even You Can Learn Statistics and Analytics: An Easy to Understand Guide

Now fully updated for 'big data' analytics and the newest applications, Even You Can Learn Statistics and Analytics, Fourth Edition is the practical, up-to-date introduction to statistics an analyticsG현for everyone!
One easy step at a time, you'll learn all the statistical techniques you'll need for finance, marketing, quality, science, social science, or anything else. Simple jargon-free explanations help you understand every technique, and realistic examples and worked problems give you all the hands-on practice you'll need. This edition contains more practical examples than everG현all updated for the newest versions of Microsoft Excel. You'll find downloadable practice files, templates, data sets, and sample modelsG현including complete solutions you can put right to work in business, school, or anywhere else. Learn how to do all this, and more:

• Apply statistical techniques to analyze huge data sets and transform them into valuable knowledge
• Construct and interpret statistical charts and tables with Excel or OpenOffice.org Calc 3
• Work with mean, median, mode, standard deviation, Z scores, skewness, and other descriptive statistics
• Use probability and probability distributions
• Work with sampling distributions and confidence intervals
• Test hypotheses with Z, t, chi-square, ANOVA, and other techniques
• Perform powerful regression analysis and modeling
• Use multiple regression to develop models that contain several independent variables
• Master specific statistical techniques for quality and Six Sigma programs

Hate math? No sweat. You'll be amazed at how little you need. Like math? Optional G푀Equation BlackboardG표 sections reveal the mathematical foundations of statistics right before your eyes! Thought you couldn't learn statistics? You canG현and you will!

List of contents

Introduction The Even You Can Learn Statistics and Analytics Owner's Manual. xiii

Chapter 1 Fundamentals of Statistics. 1

    1.1 The First Three Words of Statistics. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

    1.2 The Fourth and Fifth Words. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

    1.3 The Branches of Statistics. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

    1.4 Sources of Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

    1.5 Sampling Concepts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

    1.6 Sample Selection Methods. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

Chapter 2 Presenting Data in Tables and Charts . 15

    2.1 Presenting Categorical Variables. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

    2.2 Presenting Numerical Variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

    2.3 Bad Charts. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29

Chapter 3 Descriptive Statistics. 45

    3.1 Measures of Central Tendency. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45

    3.2 Measures of Position. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49

    3.3 Measures of Variation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54

    3.4 Shape of Distributions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59

Chapter 4 Probability. 75

    4.1 Events. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75

    4.2 More Definitions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76

    4.3 Some Rules of Probability. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78

    4.4 Assigning Probabilities. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81

Chapter 5 Probability Distributions. 87

    5.1 Probability Distributions for Discrete Variables. . . . . . . . . . . . . . . . . . . . . . . . 87

    5.2 The Binomial and Poisson Probability Distributions. . . . . . . . . . . . . . . . . . . . 93

    5.3 Continuous Probability Distributions and the Normal Distribution . . . . . . . 100

    5.4 The Normal Probability Plot. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108

Chapter 6 Sampling Distributions and Confidence Intervals. 121

    6.1 Foundational Concepts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 122

    6.2 Sampling Error and Confidence Intervals. . . . . . . . . . . . . . . . . . . . . . . . . . . 125

    6.3 Confidence Interval Estimate for the Mean Using the t Distribution (? Unknown). . . 128

    6.4 Confidence Interval Estimation for Categorical Variables . . . . . . . . . . . . . . . 131

    6.5 Confidence Interval Estimation When Normality Cannot Be Assumed. . . . . 134

Chapter 7 Fundamentals of Hypothesis Testing. 145

    7.1 The Null and Alternative Hypotheses. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 145

    7.2 Hypothesis Testing Issues. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 147

    7.3 Decision-Making Risks. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 149

    7.4 Performing Hypothesis Testing. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 150

    7.5 Types of Hypothesis Tests. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 152

Chapter 8 Hypothesis Testing: Z and t Tests. 157

    8.1 Test for the Difference Between Two Proportions . . . . . . . . . . . . . . . . . . . . . 157

    8.2 Test for the Difference Between the Means of Two Independent Groups . . . . 163

    8.3 The Paired t Test. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 168

Chapter 9 Hypothesis Testing: Chi-Square Tests and the One-Way Analysis of Variance (ANOVA). 183

    9.1 Chi-Square Test for Two-Way Tables. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183

    9.2 One-Way Analysis of Variance (ANOVA): Testing for the

    Differences Among the Means of More Than Two Groups. . . . . . . . . . . . . . . 191

Chapter 10 Simple Linear Regression. 211

    10.1 Basics of Regression Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 211

    10.2 Developing a Simple Linear Regression Model. . . . . . . . . . . . . . . . . . . . . . 214

    10.3 Measures of Variation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 221

    10.4 Inferences About the Slope. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 226

    10.5 Common Mistakes When Using Regression Analysis . . . . . . . . . . . . . . . . . 229

Chapter 11 Multiple Regression. 243

    11.1 The Multiple Regression Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 243

    11.2 Coefficient of Multiple Determination . . . . . . . . . . . . . . . . . . . . . . . . . . . . 246

    11.3 The Overall F Test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 246

    11.4 Residual Analysis for the Multiple Regression Model . . . . . . . . . . . . . . . . . 247

    11.5 Inferences Concerning the Population Regression Coefficients. . . . . . . . . . 248

Chapter 12 Introduction to Analytics. 259

    12.1 Basic Concepts. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 259

    12.2 Descriptive Analytics. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 265

    12.3 Typical Descriptive Analytics Visualizations. . . . . . . . . . . . . . . . . . . . . . . . 269

Chapter 13 Predictive Analytics. 279

    13.1 Predictive Analytics Methods. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 279

    13.2 More About Predictive Models. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 281

    13.3 Tree Induction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 284

    13.4 Clustering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 287

    13.5 Association Analysis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 290

Appendix A Microsoft Excel Operation and Configuration . 299

Appendix B Review of Arithmetic and Algebra. 301

Appendix C Statistical Tables. 311

Appendix D Spreadsheet Tips . 339

Appendix E Advanced Techniques. 343

Appendix F Documentation for Downloadable Files. 353

9780137654765, TOC, 4/25/2022

About the author

David M. Levine and David F. Stephan are part of a writing team known for their series of business statistics textbooks that include Basic Business Statistics, Business Statistics: A First Course, and Statistics for Managers Using Microsoft Excel. In long teaching careers at Baruch College, both were known for their classroom innovations, with Levine being honored with a Presidential Excellence Award for Distinguished Teaching Award and Stephan granted the privilege to design and develop the College's first computer-based classroom. Both are active members of the Data, Analytics and Statistics Instruction SIG of the Decision Sciences Institute.

Levine is Professor Emeritus of Information Systems at Baruch College. He is nationally recognized innovator in business statistics education and is also the coauthor of Applied Statistics for Engineers and Scientists Using Microsoft Excel and Minitab. Levine is also the author or coauthor of four books about statistical quality management: Statistics for Six Sigma Green Belts and Champions, Six Sigma for Green Belts and Champions, Design for Six Sigma for Green Belts and Champions, and Quality Management, 3rd Edition. He has published articles in various journals, including Psychometrika, The American Statistician, Communications in Statistics, Multivariate Behavioral Research, Journal of Systems Management, Quality Progress, and The American Anthropologist, and has given numerous talks at American Statistical Association, Decision Sciences Institute, and Making Statistics More Effective in Schools of Business conferences.

During his more than 20 years at Baruch College, Stephan devised techniques for teaching computer applications such as Microsoft Excel in a business context and developed future-forward courses that explored the effects of emerging digital technologies. He also served as the associate director of a U.S. Department of Education FIPSE project that successfully integrated interactive media into classroom instruction for the humanities.. Stephan is also the developer of PHStat, the statistics add-in for Microsoft Excel distributed by Pearson Education.

Summary

THE GUIDE FOR ANYONE AFRAID TO LEARN STATISTICS & ANALYTICS UPDATED WITH NEW EXAMPLES & EXERCISES

This book discusses statistics and analytics using plain language and avoiding mathematical jargon. If you thought you couldn't learn these data analysis subjects because they were too technical or too mathematical, this book is for you!

This edition delivers more everyday examples and end-of-chapter exercises and contains updated instructions for using Microsoft Excel. You'll use downloadable data sets and spreadsheet solutions, template-based solutions you can put right to work. Using this book, you will understand the important concepts of statistics and analytics, including learning the basic vocabulary of these subjects.

• Create tabular and visual summaries and learn to avoid common charting errors
• Gain experience working with common descriptive statistics measures including the mean, median, and mode; and standard deviation and variance, among others
• Understand the probability concepts that underlie inferential statistics
• Learn how to apply hypothesis tests, using Z, t, chi-square, ANOVA, and other techniques
• Develop skills using regression analysis, the most commonly-used Inferential statistical method
• Explore results produced by predictive analytics software
• Choose the right statistical or analytic techniques for any data analysis task
• Optionally, read the Equation Blackboards, designed for readers who want to learn about the mathematical foundations of selected methods

Product details

• Authors: David Levine, David M. Levine, David Stephan, David F. Stephan
• Publisher: Pearson Academic
• Languages: English
• Product format: Paperback / Softback
• Released: 30.09.2022
• EAN: 9780137654765
• ISBN: 978-0-13-765476-5
• No. of pages: 400
• Dimensions: 178 mm x 232 mm x 24 mm
• Weight: 680 g
• Series: Pearson Business Analytics Series
• Subjects: Natural sciences, medicine, IT, technology > Mathematics > Probability theory, stochastic theory, mathematical statistics; Social sciences, law, business > Business > General, dictionaries