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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,
1 Why Research?
What Is Research?
Impediments to Conducting Sound Research
How Can We Make Research Interesting and Persuasive?
The Research Process
2 Developing Research Questions
Selecting a Topic
From Topic to Research Question
Refining Research Questions
What Are Data?
Sources of Data
From Concepts to Variables
Forms of Data
4 Principles of Data Management
Data Cleaning and Screening
Principles of File Management
5 Finding and Using Secondary Data
Types of Secondary Data
Why Use Secondary Data?
Sources of Secondary Data
Examples of Searching for, Downloading, and Importing Data
A Simple Test of the Conceptual Model
The Pew Research Center Data
6 Primary and Administrative Data
Principles for Primary Data
Administrative Data and Linking Datasets
7 Working with Missing Data
Why Are Missing Data a Problem?
Reasons for Missing Data
Types of Missing Data
Forms and Patterns of Missing Data
Addressing Missing Data in the Analysis Stage
8 Principles of Data Presentation
First Principles: Clarity, Precision, and Efficiency
Why Words Are Not Enough
Types of Tables and Graphics
Principles of Data Presentation
9 Designing Tables for Data Presentations
Table or Graphic?
Examples of Tables
10 Designing Graphics for Data Presentations
Examples of Graphics
Where to Next?
Appendix: Introduction to Statistical Software
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.