Abstract
Quantitative data quality assurance is the systematic process and procedures used to ensure the accuracy, consistency, reliability, and integrity of data throughout the research process. Effective quality assurance helps identify and correct errors, reduce biases, and ensure the data meets the standards needed for analysis and reporting. This paper provides an overview of key issues to consider when working with data and reporting findings.
Published Version
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