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Principles of Statistical Data Handling

Autor Fred Davidson
en Limba Engleză Paperback – 29 mai 1996
This book will help the reader understand the principles of data handling and make better use of computer data in research or study. It demonstrates how to input, manipulate and debug 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, 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.
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Specificații

ISBN-13: 9780761901037
ISBN-10: 0761901035
Pagini: 336
Dimensiuni: 152 x 229 x 21 mm
Greutate: 0.54 kg
Ediția:1
Editura: SAGE Publications
Colecția Sage Publications, Inc
Locul publicării:Thousand Oaks, United States

Recenzii

"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." 

"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." 

Cuprins

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

Descriere

Fred Davidson demonstrates how to input, manipulate and debug data to make substantive analysis easier and more accurate. 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.