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Best practices in data cleaning : a complete guide to everything you need to do before and after collecting your data

Author: Jason W Osborne
Publisher: Thousand Oaks, Calif. : SAGE, ©2013.
Edition/Format:   Print book : EnglishView all editions and formats
Database:WorldCat
Summary:
"Many researchers jump straight from data collection to data analysis without realizing how analyses and hypothesis tests can go profoundly wrong without clean data. This book provides a clear, step-by-step process to examining and cleaning data in order to decrease error rates and increase both the power and replicability of results. Jason W. Osborne, author of Best Practices in Quantitative Methods (SAGE, 2008)  Read more...
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Document Type: Book
All Authors / Contributors: Jason W Osborne
ISBN: 9781412988018 1412988012
OCLC Number: 730403666
Description: xv, 275 pages : illustrations ; 23 cm
Contents: Why data cleaning is important: debunking the myth of robustness --
Power and planning for data collection: debunking the myth of adequate power --
Being true to the target population: debunking the myth of representativeness --
Using large data sets with probability sampling frameworks: debunking the myth of equality --
Screening your data for potential problems: debunking the myth of perfect data --
Dealing with missing or incomplete data: debunking the myth of emptiness --
Extreme and influential data points: debunking the myth of equality --
Improving the normality of variables through box-cox transformation: debunking the myth of distributional irrelevance --
Does reliability matter? debunking the myth of perfect measurement --
Random responding, motivated misresponding, and response sets: debunking the myth of the motivated participant --
Why dichotomizing continuous variables is rarely a good practice: debunking the myth of categorization --
The special challenge of cleaning repeated measures data: lots of pits in which to fall --
Now that the myths are debunked: visions of rational quantitative methodology for the 21st century
Responsibility: Jason W. Osborne.

Abstract:

This book provides a clear, step-by-step process of examining and cleaning data in order to decrease error rates and increase both the power and replicability of results.  Read more...

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"This book provides the perfect bridge between the formal study of statistics and the practice of statistics. It fills the gap left by many of the traditional texts that focus either on the technical Read more...

 
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