Statistics for Dummies (4 page)
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Stymied by statistics? No fear—this friendly guide offers clear, practical explanations of statistical ideas, techniques, formulas, and calculations, with lots of examples that show how these concepts apply to your everyday life. You’ll see how to take the margin of error out of opinion polls and how to analyze and interpret data for improved classroom or on-the-job performance. Discover how to:
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About the Author Deborah Rumsey earned her Ph.D. in statistics from Ohio State University (OSU) in 1993. Upon graduating, she joined the faculty in the Department of Statistics at Kansas State University, winning the distinguished Presidential Teaching Award and earning tenure and promotion in 1998. In 2000, she returned to OSU as the Director of the Mathematics and Statistics Learning Center, where she is today. Deb is the Editor of the “Teaching Bits” of the |
Ph.D.
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About the Author
Deborah Rumsey earned her Ph.D. in statistics from Ohio State University (OSU) in 1993. Upon graduating, she joined the faculty in the Department of Statistics at Kansas State University, winning the distinguished Presidential Teaching Award and earning tenure and promotion in 1998. In 2000, she returned to OSU as the Director of the Mathematics and Statistics Learning Center, where she is today. Deb is the Editor of the "Teaching Bits" of the
Journal of Statistics Education;
she has also published papers and given professional presentations on the subject of statistics education, with a particular emphasis on statistical literacy (skills for understanding statistics in everyday life and the workplace) and immersive learning environments (environments that promote students' discovery of ideas on their own). Her passions include fishing, bird watching, and Ohio State Buckeye football (not necessarily in that order).
Dedication
To my husband, Eric, and my son, Clint Eric: You are my greatest teachers.
Author's Acknowledgments
I'd like to thank the people that made this book possible: Kathy Cox, for asking me to write the book I'd always dreamed of writing; Tere Drenth, for handling my dream with just the right touch to make sure it was finished on time and in the right format; Janet Dunn, for her thorough copyedit; John Gabrosek, Grand Valley State University, for his thorough technical review. Also, many thanks for the Composition Services department at Wiley Publishing, Inc., who created all of the equations in this book and managed the difficult layout issues beautifully.
To Peg Steigerwald, Mike O'Leary, and my colleague Jim Higgins: The many scribbling-on-a-napkin conversations we've had about statistics helped shape the way I think and talk about it. Thank you for making it real and for cheering me on. Thanks to Tony Barkauskas, UW-LaCrosse, the first and best professor I ever had, for inspiring me. I am so grateful to my friends in the Department of Statistics and the Mathematics and Statistics Learning Center at Ohio State who gave me constant support and encouragement. And a big thank you to my family for their love and faith in me.
Publisher's Acknowledgments
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The purpose of this book is to get you ready to sort through and evaluate the incredible amount of statistical information that comes to you on a daily basis. (You know the stuff: charts, graphs, tables, as well as headlines that talk about the results of the latest poll, survey, experiment, or other scientific study.) This book arms you with the ability to decipher and make important decisions about statistical results (for example, the results of the latest medical studies), being ever aware of the ways in which people can mislead you with statistics and how to handle them.
This book is chock-full of real examples from real sources that are relevant to your everyday life: from the latest medical breakthroughs, crime studies, and population trends to surveys on Internet dating, cellphone use, and the worst cars of the millennium. By reading the chapters in this book, you begin to understand how to use charts, graphs, and tables, and you also know how to examine the results of the latest polls, surveys, experiments, or other studies. You even find out how to use crickets to gauge temperature and how to win a bigger jackpot in the lottery.
You also get to enjoy poking a little fun at statisticians (who take themselves too seriously at times). And that's because you don't have to be a statistician to understand statistics.
This book departs from traditional statistics texts, references, supplement books, and study guides in the following ways:
Practical and intuitive explanations of statistical concepts, ideas, techniques, formulas, and calculations.
Clear and concise step-by-step procedures that intuitively explain how to work through statistics problems.
Interesting real-world examples relating to your everyday life and workplace.
Upfront and honest answers to your questions like, "What does this really mean?" and "When and how I will ever use this?"
I have three conventions that you should be aware of as you make your way through this book.
Definition of sample size(
n
):
When I refer to the size of a sample, I usually mean the number of individuals selected to participate in a survey, study, or experiment. (The notation for sample size is
n.
) Suppose, however, that 100 people were
selected
to participate in a survey, and only 80 of them
responded:
Which of these two numbers is
n:
100 or 80? The convention I use is 80, the number of people who actually responded, and this number may be fewer than the number asked to participate. So, any time you see the phrase "sample size", think of it as the final number of individuals who participated in and provided information for the study.Dual-use of the word "statistics":
In some situations, I refer to statistics as a subject of study, or as a field of research, so the word is a singular noun. For example, "Statistics is really quite an interesting subject." In other situations, I refer to statistics as the plural of statistic, in a numerical sense. For example, "The most common statistics are the mean and the standard deviation."Use of the word "data":
You're probably unaware of the debate raging amongst statisticians about whether the word "data" should be singular ("data is
…
") or plural ("data are
…
"). It got so bad that one group of statisticians had to develop two different versions of a statistics T-shirt recently: "Messy Data Happens" and "Messy Data Happen." At the risk of offending some of my colleagues, I'm going to go with the plural version of the word data in this book, because the word "data" is and will always be a plural noun (at least that's what my editor tells me).
