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Principles of Statistical Data Handling
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Principles of Statistical Data Handling


April 1996 | 336 pages | SAGE Publications, Inc
ABOUT THE APPROACH "I like the stress on a 'principled approach' to data handling. The author makes clear that data analysts need to be thoughtful, careful, and reflective; data handling is not viewed as simply a mechanical or routine activity." --George Engelhard Jr., Emory University GENERAL "Principles of Statistical Data Handling deals with the most neglected aspect of implementing a quantitative research design, that is preparing the data for statistical analysis. Because this part of the process is so often neglected it is the most common source of trouble when a quantitative research project crashes, produces gibberish, and has to be done all over again. Remarkably, the author writes an interesting and easy-to-read book on what might seem an irredeemably dreary and technical topic. I will recommend this book to almost every one of my students who plans to do a dissertation using quantitative data." W. Paul Vogt, State University of New York, Albany "Many of the topics and strategies covered in this text are very realistic, and most of us that have been involved in data analysis over the years can relate to the data handling problems mentioned in the text; the author has done an excellent job of sharing his wisdom from many years of practical work as a data analyst." --George Engelhard Jr., Emory University ABOUT THE WRITING STYLE "The writing style is clearly informal. The author speaks to the reader as a good teacher speaks to a student." --Robert F. DeVellis, The University of North Carolina, Chapel Hill "There is a delightful humor that comes through in this book and a playfulness that I enjoyed. The pace and level is appropriate for an introduction to data handling." --John W. Creswell, University of Nebraska, Lincoln ABOUT THE PEDAGOGY "The discussion questions are very, very good. I particularly like the idea of suggesting that the reader/student interact with some 'outsiders.'" --Carl J. Huberty, The University of Georgia Faulty data can lead to faulty conclusions, and because data often concern people--that can mean faulty conclusions about people. Aimed at helping readers understand the principles of data handling so that they can make better use of computer data in their research and studies, Principles of Statistical Data Handling shows readers how to input, manipulate, and debug their data to make substantive analysis easier and more accurate. Using a series of principles, universal concepts that apply no matter what the data gathering context or computer software, author Fred Davidson presents a situation or a problem, suggests how it might be resolved, and demonstrates the implementation of each principle as it appears in the command languages of SAS and SPSS. This volume is essential for graduate courses in data analysis or research methods taught out of psychology, education, and sociology departments. Researchers in these areas who want to brush-up on their techniques will also find Principles of Statistical Data Handling an indispensable book.

 
Introduction
A Principled Approach

 
 
Data Input
 
Data Manipulation
 
Data Debugging
 
Data Aspects of Statistical Analysis
 
The `End' of Data Handling
 
Conclusion
Data Handling Story-Problems

 

"Have you ever read and said to yourself, ‘Boy, I wish I had that back then?’ In the area of data handling and manipulation, this is that book." 

H. Gary Cook
Michigan State University

"Principles of Statistical Data Handling deals with the most neglected aspects of implementing a quantitative research design, that is, preparing the data for statistical analysis. Because this part of the process is so often neglected, it is the most common source of trouble when a quantitative research project crashes, produces gibberish, and has to be done all over again. Remarkably, the author writes an interesting and easy-to-read book on what might seem an irredeemably dreary and technical topic. I will recommend this book to almost every one of my students who plans to do a dissertation using quantitative data." 

W. Paul Vogt
State University of New York, Albany

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