Principles of Data Management and Presentation - Hardcover

Hoffmann, John P.

 
9780520289956: Principles of Data Management and Presentation

Inhaltsangabe

The world is saturated with data. We are regularly presented with data in words, tables, and graphics. Students from many academic fields are now expected to be educated about data in one form or another. Yet the typical sequence of courses—introductory statistics and research methods—does not provide sufficient information about how to focus in on a research question, how to access data and work with datasets, or how to present data to various audiences.
  
Principles of Data Management and Presentation addresses this gap. Assuming only that students have some familiarity with basic statistics and research methods, it provides a comprehensive set of principles for understanding and using data as part of a research project, including:
• how to narrow a research topic to a specific research question
• how to access and organize data that are useful for answering a research question
• how to use software such as Stata, SPSS, and SAS to manage data
• how to present data so that they convey a clear and effective message
 
A companion website includes material to enhance the learning experience—specifically statistical software code and the datasets used in the examples, in text format as well as Stata, SPSS, and SAS formats. Visit www.ucpress.edu/go/datamanagement, Downloads tab. 

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Über die Autorin bzw. den Autor

John P. Hoffmann is Professor of Sociology at Brigham Young University. Before arriving at BYU, he was a senior research scientist at the National Opinion Research Center (NORC), a nonprofit firm affiliated with the University of Chicago. He received a master’s in Law and Justice from American University and a doctorate in Criminal Justice from SUNY–Albany. He also received a master’s in Public Health with emphases in Epidemiology and Behavioral Sciences at Emory University. His research addresses drug use, juvenile delinquency, and the sociology of religion.
 

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Principles of Data Management and Presentation

By John P. Hoffmann

UNIVERSITY OF CALIFORNIA PRESS

Copyright © 2017 The Regents of the University of California
All rights reserved.
ISBN: 978-0-520-28995-6

Contents

Preface,
Acknowledgments,
1 Why Research?,
2 Developing Research Questions,
3 Data,
4 Principles of Data Management,
5 Finding and Using Secondary Data,
6 Primary and Administrative Data,
7 Working with Missing Data,
8 Principles of Data Presentation,
9 Designing Tables for Data Presentations,
10 Designing Graphics for Data Presentations,
Appendix: Introduction to Statistical Software,
References,
Index,


CHAPTER 1

Why Research?


It seems that every day brings another report of some research finding. A quick Internet search of news articles that appeared on an otherwise ordinary day in June revealed, among other stories, that California just approved a publicly funded gun research center, the Netherlands began a campaign to identify and reduce research misconduct, a geological study discovered that some parts of the San Andreas Fault are sinking and others are rising, a nutrition study suggested that broccoli is healthier than previously thought because its phenolic compounds have notable antioxidant properties, and a survey revealed that about 31% of people admit to snooping on a friend or loved one by looking at their cell phones. As suggested by just a single day's news coverage, research is a huge enterprise, employing millions of people worldwide and resulting in thousands of reports, articles, and books every year. The American Association for the Advancement of Science (2016) estimates that the US government spends about $70 billion per year on various forms of research.

But many people have questioned the value of some of this funded research. We regularly see debates about the value of research on global warming, firearms, health-care systems, and many other topics. In addition, conservative politicians such as US Senator Tom Coburn of Oklahoma publish annual reports of federal government waste, taking particular glee in pointing out what are considered dubious scientific studies. For example, the 2014 Wastebook highlights studies of gambling monkeys, mountain lions on treadmills, and synchronized swimming by brine shrimp. Yet, there is clearly much to be gained from good research. Without it, there is little doubt that death, illness, and injury rates would be much higher. Food production would be substantially lower. The field of forensic science would be much more primitive, thus impeding efforts to solve crimes and catch criminals. Producing enough power to light homes, operate cars, and run businesses would be much more difficult. The list goes on and on.

Social science often gets a particularly bad rap because some do not consider it a true "science." But it has also contributed not only to making the world a better place, but also to increasing our understanding of the way people, social groups, communities, and institutions function and interact. Let's examine a few examples of social science research to see what it has taught us. As you read the following illustrations, think of what broader implications each has for understanding the social world and perhaps even improving people's lives.

In the mid-1960s, the social psychologist Stanley Milgram wanted to determine how close or far apart people were socially. He devised a project in which he mailed a letter to random people who lived in several Midwestern US cities. The letter asked them if they personally knew an individual — again selected randomly — who lived in Boston, Massachusetts. If they did, they were to send the letter to this person. If not, they were to send the letter to a friend or relative who was more likely to know the person in Boston. He then examined how many times, on average, the letters that reached the person had been sent. This led to the famous phrase about "six degrees of separation," which was based on the average number of times the letter was forwarded (Milgram 1967). Even though the project and its findings have been criticized in the ensuing years (Watts 2004), it has motivated hundreds of subsequent studies on social networks and led to the proliferation of social network analysis as a valuable research tool for the social sciences. In what other ways might social networks be important for understanding the way people interact and how this affects their lives?

In the early 1990s, political scientist Bruce Keith and his colleagues wished to understand better what it means to be a political independent. Whereas many people in the United States identify as a Democrat or a Republican, a plurality claim they are independent and don't identify with either political party. Understanding what this signifies has important implications for voting behavior and the public's support of political figures and their policies. Keith et al. (1992) determined that a large number of independents are actually fairly consistent in voting for Democratic or Republican candidates. Thus, regardless of how they label themselves, only a relatively small percentage of voters are truly "independent." What might this finding suggest for other questions about how people identify with groups and engage in civic life?

Finally, most residents of a town or city can distinguish the "good" neighborhoods from the "bad" neighborhoods. Good neighborhoods tend to be safe, whereas bad neighborhoods tend to be dangerous, places where the risk of falling victim to crime is high. Often, we perceive of bad neighborhoods as those with vacant lots, graffiti, and boarded-up buildings. Sociologists Robert Sampson and Stephen Raudenbush (2004) sought to understand whether these signs of "disorder" were valid markers of dangerous areas. By carefully studying dozens of Chicago neighborhoods, they found that it was less the explicit "dangerousness" of a neighborhood — as measured by criminal activity or physical decay — that predicted whether people judged a neighborhood as qualitatively bad or good, but instead whether there was more poverty and minorities who lived in a neighborhood. In other words, neighborhoods can get labeled as bad or good based on the types of people who live in them, regardless of how objectively safe they are. What consequences does this finding have for understanding social and ethnic relationships, the health and development of communities, and how the criminal justice system operates?

I hope it is clear that each of these studies, while important in its own right, illustrates the value of social science research. We know that scientific research has led to many improvements in the world, from longer lives due to medical advances to rapid transit from one part of the globe to another. Although perhaps not considered as beneficial, research in the social and behavioral sciences has also led to a better understanding of society, with the potential to improve lives, relationships, and communities. For example, social network studies, many of which are motivated by Stanley Milgram's research, have led to more effective health education and intervention programs (e.g., Kim et al. 2015), thus serving to improve health among underserved groups of people. Sampson and Raudenbush's study might lead to more just policing strategies and help prevent police shootings in minority neighborhoods (a problem that has plagued several US communities over the past few years).


WHY RESEARCH?

Although most of us will never conduct research...

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9780520289949: Principles of Data Management and Presentation

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ISBN 10:  0520289943 ISBN 13:  9780520289949
Verlag: University of California Press, 2017
Softcover