What is the purpose of data triangulation in research?

What is the purpose of data triangulation in research?

• A. To increase the complexity of data analysis.
• B. To focus solely on one data source for conclusions.
• C. To strengthen research findings by validating results through multiple data sources.
• D. To filter out insignificant data.

Answer: (C)

The purpose of data triangulation in research is to strengthen findings by validating results through multiple data sources. This approach enhances the credibility and reliability of research outcomes by providing a comprehensive perspective on the studied phenomenon. By using different sources of data, researchers can confirm their findings and mitigate biases that may arise from relying on a single source. Triangulation helps to ensure that the conclusions drawn from the study are not simply artifacts of a particular dataset, but rather reflect a more nuanced understanding of the research question. This multifaceted approach often leads to richer insights and a deeper understanding of complex issues, promoting greater confidence in the research conclusions.

The purpose of data triangulation in research is to strengthen findings by validating results through multiple data sources. This approach enhances the credibility and reliability of research outcomes by providing a comprehensive perspective on the studied phenomenon. By using different sources of data, researchers can confirm their findings and mitigate biases that may arise from relying on a single source. Triangulation helps to ensure that the conclusions drawn from the study are not simply artifacts of a particular dataset, but rather reflect a more nuanced understanding of the research question. This multifaceted approach often leads to richer insights and a deeper understanding of complex issues, promoting greater confidence in the research conclusions.