AI Article Synopsis
- Quantitative data quality assurance is a set of systematic processes that ensure the accuracy and reliability of data in research.
- It helps to identify and correct errors, reduce biases, and maintain the integrity of data for effective analysis and reporting.
- The paper discusses important considerations for managing data quality and reporting research findings.
Article 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.
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| http://dx.doi.org/10.1111/jpm.13143 | DOI Listing |
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