Basic Statistics for Social Research

Robert A. Hanneman, Augustine J. Kposowa, Mark D. Riddle

• Publisher: Jossey-Bass
• Year: 2012
• Print ISBN: 9780470587980
• eBook ISBN: 9781118234150
• Edition: 1
• Topic: Education
• Subtopic: Evaluation & Assessment in Education

A core statistics text that emphasizes logical inquiry, not math

Basic Statistics for Social Research teaches core general statistical concepts and methods that all social science majors must master to understand (and do) social research. Its use of mathematics and theory are deliberately limited, as the authors focus on the use of concepts and tools of statistics in the analysis of social science data, rather than on the mathematical and computational aspects. Research questions and applications are taken from a wide variety of subfields in sociology, and each chapter is organized around one or more general ideas that are explained at its beginning and then applied in increasing detail in the body of the text.

Each chapter contains instructive features to aid students in understanding and mastering the various statistical approaches presented in the book, including:

• Learning objectives
• Check quizzes after many sections and an answer key at the end of the chapter
• Summary
• Key terms
• End-of-chapter exercises
• SPSS exercises (in select chapters)

Ancillary materials for both the student and the instructor are available and include a test bank for instructors and downloadable video tutorials for students.

PART I
Univariate Description

Chapter 1
Using Statistics

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LEARNING OBJECTIVES

When you have finished this chapter, you will be able to:

• Distinguish the uses of statistics for description, inference, hypothesis testing, and prediction.
• Distinguish between the exploratory and confirmatory uses of statistics.
• Understand the distinction between sample statistics and population parameters.
• Understand how statistics are related to the process of constructing and verifying theory.
• Know how to write a report using statistical information.
• Identify units of analysis and cases in research problems.
• Understand variables and apply the notion of levels of measurement.

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WHY STUDY STATISTICS?

Whether you wish it or not, you are a consumer of statistics. The news media present a constant flow of information, with government officials and pundits often throwing out number after number, ranging from current unemployment figures to opinion poll results about how some administration is doing in office. During football season, colleges are ranked based on polling coaches and feeding statistical data into computers. In newspapers, leading economic indicators, corporate performance and profits, results of studies both social and medical, car sales, and weather forecasts are all presented to the public in statistical language.

How does one process information and cope with the relentless barrage of statistical data without becoming overwhelmed? And, perhaps even more importantly, how does one become an intelligent and critical user of statistical information? Statistics are used not only to inform us, but to influence us. As a common aphorism puts it: “Statistics don’t lie, but liars use statistics.”

For a student of statistics, the answer lies in becoming an informed and discerning user of numerical information. The job of a student of statistics is to derive useful and usable information from a flood of data too large and complicated to be understood without being summarized. Learning to discern what is essential and what is not in quantitative data is an art and craft that requires practice and experience. But it is cultivated through careful learning. Some people devote their entire careers to accomplishing this and becoming experts—for example, university professors. Unless he or she is a statistics major, an undergraduate student does not have the time to devote a career to learning statistics in the four years of study for the BA or BS degree. Nevertheless, the crucial tools of becoming an informed user of statistical data can be learned in an introductory-level course in statistics in the time span of a quarter or a semester.

This book has been written to guide you through your first course in statistics at the undergraduate level. The only assumption that the authors have made is that everyone is capable of learning statistics. Accordingly, the book is not a textbook in mathematics. Formulas have been kept to a minimum. Where their use is unavoidable, the authors have gone to great lengths to explain every component and guide you through their application. Mathematical proofs are deliberately avoided throughout the book. Students who wish to learn proofs and acquire higher levels of statistics knowledge will find many courses on their campus that will satisfy their intellectual curiosity. The goal of the book is to help you learn and become an informed user of statistics whether your eventual plan is to obtain a degree and get employed or to undertake graduate work.

TASKS FOR STATISTICS: DESCRIBING, INFERRING, TESTING, PREDICTING

A first step in learning statistics is to appreciate the human capacity to summarize information through visual inspection and numerical indicators. Graphs and other charts can be used to summarize lots of information that would require many pages if each piece of information were written down without graphs. Through visual inspection, the statistician can begin to look for patterns or trends in data to explore the possibility of uncovering relationships. In addition to visual inspection, the statistician uses simple arithmetic to compute single numbers (indexes or numerical indicators) that summarize data and buttress results derived from visual gleaning.

Having described the data in summary form, the next major goal of the statistician is to draw inferences or arrive at conclusions using simple mathematical calculations. In an increasingly complex world, rarely do researchers use the entire population or universe of cases to conduct a study. Instead, they use a ...

Table of contents

• Cover
• Table of Contents
• Title
• Copyright
• Tables and Figures
• Preface
• About the Authors
• Part I: Univariate Description
• Part II: Inference and Hypothesis Testing
• Part III: Association and Prediction
• Appendix
• Index
• End User License Agreement