Best Practices in Data Cleaning
A Complete Guide to Everything You Need to Do Before and After Collecting Your Data
- Jason W. Osborne - Clemson University, USA
Quantitative Methods
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) provides easily-implemented suggestions that are research-based and will motivate change in practice by empirically demonstrating for each topic the benefits of following best practices and the potential consequences of not following these guidelines. If your goal is to do the best research you can do, draw conclusions that are most likely to be accurate representations of the population(s) you wish to speak about, and report results that are most likely to be replicated by other researchers, then this basic guidebook is indispensible.
“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 presentation or recipe-driven presentation of topics.”
“The first comprehensive and generally accessible text in this area.”
Sample Materials & Chapters
Chapter 1: Why Data Cleaning is Important
Chapter 6: Dealing with Missing or Incomplete Data