Even You Can Learn Statistics: A Guide for Everyone Who Has Ever Been Afraid of Statistics, 2nd Edition
- By David M. Levine, David F. Stephan
- Published Aug 17, 2009 by FT Press.
- Copyright 2010
- Dimensions: 7 X 9-1/4
- Pages: 384
- Edition: 2nd
- Book
- ISBN-10: 0-13-701059-1
- ISBN-13: 978-0-13-701059-2
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Product Author Bios
David M. Levine, a much-honored innovator in statistics education, is Professor Emeritus of Statistics and Computer Information Systems at Baruch College (CUNY). His bestselling books include Statistics for Managers Using Microsoft Excel, Basic Business Statistics, Business Statistics: A First Course, Statistics for Six Sigma Green Belts with Minitab and JMP, Six Sigma for Green Belts and Champions, and Design for Six Sigma for Green Belts and Champions.
David F. Stephan is an independent instructional technologist. As a computer information systems instructor at Baruch College (CUNY), he pioneered the use of computers in classrooms, devised interdisciplinary multimedia tools, and created techniques for teaching computer applications in a business context. The developer of PHStat2, the Pearson Education statistics add-in system for Microsoft Excel, he has coauthored several books with David M. Levine.
Even You Can Learn Statistics: A Guide for Everyone Who Has Ever Been Afraid of Statisticsi s a practical, up-to-date introduction to statistics—for everyone! Thought you couldn’t learn statistics? You can—and you will! One easy step at a time, this fully updated book teaches you all the statistical techniques you’ll need for finance, quality, marketing, the social sciences, or anything else! Simple jargon-free explanations help you understand every technique. Practical examples and worked-out problems give you hands-on practice. Special sections present detailed instructions for developing statistical answers, using spreadsheet programs or any TI-83/TI-84 compatible calculator. This edition delivers new examples, more detailed problems and sample solutions, plus an all-new chapter on powerful multiple regression techniques. Hate math? No sweat. You’ll be amazed at how little you need. Like math? Optional “Equation Blackboard” sections reveal the mathematical foundations of statistics right before your eyes! You’ll learn how to:
• 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
About the Web Site
Download practice files, templates, data sets, and sample spreadsheet models—including ready-to-use solutions for your own work! www.ftpress.com/youcanlearnstatistics2e
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12 of 12 people found the following review helpful
So-so, By
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This review is from: Even You Can Learn Statistics: A Guide for Everyone Who Has Ever Been Afraid of Statistics (2nd Edition) (Paperback)
This book tries to break down statistics into an understandable format, but I learn best by doing. While the book has sample problems for you to work out, the answers do not come with explanations, so if you didn't get it right the first time, you have no idea where you went wrong.
5 of 6 people found the following review helpful
Memorize and take a test.,
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This review is from: Even You Can Learn Statistics: A Guide for Everyone Who Has Ever Been Afraid of Statistics (2nd Edition) (Kindle Edition)
The book is factual and if you can wade through it, useful. The writing has a social/political attitude, which is slightly annoying. But the problem with the book is that it starts by giving about 20 words for which you must memorize the definitions assigned to them within this specific profession or discipline, which is not the common English definition. A good editor who also knows how to write could turn this into a real gem by starting with examples and pivoting off those to an explanation of what the various elements are and how they affect each other. But I admire and respect anyone who can write a book and I applaud the author.
1 of 1 people found the following review helpful
Just not a well written book, By Helene Gray (New York, NY United States) - See all my reviews
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This review is from: Even You Can Learn Statistics: A Guide for Everyone Who Has Ever Been Afraid of Statistics, Enhanced Edition (Kindle Edition with Audio/Video)
I had to buy this book for a class. It is just not well written. I am three chapters in and have found multiple formula errors. It makes studying more difficult when the example that is supposed to explain a concept is referring to another concept or doesn't work out mathematically. I use this to find out what the teacher wants for the assignments and I use another book to clarify the concepts this one is trying to explain.
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Online Sample Chapter
Table of Contents
Acknowledgments. . . . . viii
About the Authors . . . . . ix
Introduction The Even You Can Learn Statistics Owners Manual. . . . xi
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 . . . . . 5
1.4 Sources of Data . . . . . 6
1.5 Sampling Concepts . . . . 7
1.6 Sample Selection Methods. . . . . 9
Chapter 2 Presenting Data in Charts and Tables. . . . . 19
2.1 Presenting Categorical Variables. . . . . . 19
2.2 Presenting Numerical Variables. . . . .. 26
2.3 Misusing Charts. . . . . 32
Chapter 3 Descriptive Statistics . . . . 43
3.1 Measures of Central Tendency . . . . 43
3.2 Measures of Position. . . . . 47
3.3 Measures of Variation. . . . . . 51
3.4 Shape of Distributions . . . . . 57
Chapter 4 Probability . . . . . . 71
4.1 Events. . . . . . 71
4.2 More Definitions . . . . . . 72
4.3 Some Rules of Probability . . . . . 74
4.4 Assigning Probabilities . . . . 77
Chapter 5 Probability Distributions . . . . 83
5.1 Probability Distributions for Discrete Variables . . .. . 83
5.2 The Binomial and Poisson Probability Distributions. . . . 89
5.3 Continuous Probability Distributions and the Normal Distribution . . . 97
5.4 The Normal Probability Plot. . . . . 105
Chapter 6 Sampling Distributions and Confidence Intervals . . . . 119
6.1 Sampling Distributions. . . . . . . 119
6.2 Sampling Error and Confidence Intervals. . . . . . 123
6.3 Confidence Interval Estimate for the Mean Using the t Distribution (ó Unknown) . . . . . 127
6.4 Confidence Interval Estimation for Categorical Variables. .. . . 131
Chapter 7 Fundamentals of Hypothesis Testing . . . 141
7.1 The Null and Alternative Hypotheses. . . . . . 141
7.2 Hypothesis Testing Issues . . . . . 143
7.3 Decision-Making Risks . . . . . . . 145
7.4 Performing Hypothesis Testing . . . . . 147
7.5 Types of Hypothesis Tests . . . . 148
Chapter 8 Hypothesis Testing: Z and t Tests . . . . 153
8.1 Testing for the Difference Between Two Proportions. . . . . . 153
8.2 Testing for the Difference Between the Means of Two Independent Groups .. . . . . . 160
8.3 The Paired t Test . . . . . 166
Chapter 9 Hypothesis Testing: Chi-Square Tests and the One-Way Analysis of Variance (ANOVA). . . . . .179
9.1 Chi-Square Test for Two-Way Cross-Classification Tables . . . . . 179
9.2 One-Way Analysis of Variance (ANOVA): Testing for the Differences Among the Means of More Than Two Groups . . . . 186
Chapter 10 Simple Linear Regression . . . . . ..207
10.1 Basics of Regression Analysis . . . . . . . 208
10.2 Determining the Simple Linear Regression Equation . . . . . . 209
10.3 Measures of Variation . . . . . . 217
10.4 Regression Assumptions. . . . . . . . . 222
10.5 Residual Analysis. . . . . . .223
10.6 Inferences About the Slope. . . . . 225
10.7 Common Mistakes Using Regression Analysis . . . . . 228
Chapter 11 Multiple Regression . . . . . ..245
11.1 The Multiple Regression Model . . . . . 245
11.2 Coefficient of Multiple Determination. . . . . . 248
11.3 The Overall F test. . . . . . . 249
11.4 Residual Analysis for the Multiple Regression Model . . . . . . 250
11.5 Inferences Concerning the Population Regression Coefficients . . . . 251
Chapter 12 Quality and Six Sigma Applications of Statistics . . . . 265
12.1 Total Quality Management . . . . . 265
12.2 Six Sigma. . . . . . . 267
12.3 Control Charts . . . . . 268
12.4 The p Chart. . . . . . .271
12.5 The Parable of the Red Bead Experiment: Understanding Process Variability . . . . . . . . 276
12.6 Variables Control Charts for the Mean and Range . . . . . 278
Appendix A Calculator and Spreadsheet Operation and Configuration . . . . ..295
A.C1 Calculator Operation Conventions ...... 295
A.C2 Calculator Technical Configuration ...... 297
A.C3 Using the A2MULREG Program ...... 298
A.C4 Using TI Connect ...... 298
A.S1 Spreadsheet Operation Conventions ..... 299
A.S2 Spreadsheet Technical Configurations..... 299
Appendix B Review of Arithmetic and Algebra . . . . .301
Assessment Quiz . . . . . . 301
Symbols. . . . . 304
Answers to Quiz. . . . . . . 310
Appendix C Statistical Tables . . . 311
Appendix D Spreadsheet Tips. . . . . . ..339
CT: Chart Tips . . . . . 339
FT: Function Tips . . . . .341
ATT: Analysis ToolPak Tips (Microsoft Excel only). . . . .343
Appendix E Advanced Techniques. . . . . . 347
E.1 Using PivotTables to Create Two-Way Cross-Classification Tables . . . . 347
E.2 Using the FREQUENCY Function to Create Frequency Distributions. . . . . . . 349
E.3 Calculating Quartiles . . . . . . 350
E.4 Using the LINEST Function to Calculate Regression Results. . . . . 351
Appendix F Documentation for Downloadable Files . . . . 353
F.1 Downloadable Data Files . . . . . . 353
F.2 Downloadable Spreadsheet Solution Files. . . . . . 357
Glossary . . . . ..359
Index . . . . .367
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