Location
University of Nevada, Las Vegas
Start Date
16-4-2011 2:00 PM
End Date
16-4-2011 3:30 PM
Description
Data quality is critical to reaching correct research conclusions. Researchers attempt to ensure that they have accurate data by checking the data after it has been entered. Previous research has demonstrated that some methods of data checking are better than others, but not all researchers use the best methods. Perhaps researchers continue to use less optimal data checking methods because they mistakenly believe that they are highly accurate. The purpose of this study was to examine the relationship between perceived data quality and actual data quality. A total of 29 participants completed this study. Participants checked that letters and numbers had been entered correctly into the computer using one of three randomly assigned data checking methods. Afterwards, they rated the quality of their data checking method. The sample correlations between perceived and actual data quality were small to moderate and confidence intervals for the population correlations did not include high values. We conclude that the relationship between actual and perceived data quality is not high.
Keywords
Data editing; Data integrity; Quality control; Research
Disciplines
Cognition and Perception | Design of Experiments and Sample Surveys | Multivariate Analysis | Quantitative, Qualitative, Comparative, and Historical Methodologies
Language
English
Included in
Cognition and Perception Commons, Design of Experiments and Sample Surveys Commons, Multivariate Analysis Commons, Quantitative, Qualitative, Comparative, and Historical Methodologies Commons
Relationship between perceived and actual quality of data checking
University of Nevada, Las Vegas
Data quality is critical to reaching correct research conclusions. Researchers attempt to ensure that they have accurate data by checking the data after it has been entered. Previous research has demonstrated that some methods of data checking are better than others, but not all researchers use the best methods. Perhaps researchers continue to use less optimal data checking methods because they mistakenly believe that they are highly accurate. The purpose of this study was to examine the relationship between perceived data quality and actual data quality. A total of 29 participants completed this study. Participants checked that letters and numbers had been entered correctly into the computer using one of three randomly assigned data checking methods. Afterwards, they rated the quality of their data checking method. The sample correlations between perceived and actual data quality were small to moderate and confidence intervals for the population correlations did not include high values. We conclude that the relationship between actual and perceived data quality is not high.