Triangulation
Triangulation is a method used in data science to improve the accuracy and reliability of results by combining multiple methods or data sources. It involves the use of at least three independent sources of data or methods to verify or cross-check the results obtained from each. Triangulation can be used in various stages of the data analysis process, including data collection, analysis, and interpretation. By using multiple sources or methods, triangulation helps to reduce the risk of bias, errors, or inconsistencies in the data or analysis. It also helps to increase the validity and generalizability of the findings, as well as to identify potential areas of disagreement or inconsistency that require further investigation.
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