What does data triangulation in research imply?

What does data triangulation in research imply?

• A. Using a single source of data
• B. Combining different research methods for validation
• C. Analyzing quantitative data exclusively
• D. Focusing only on qualitative interviews

Answer: (B)

Data triangulation in research refers to the practice of combining multiple methodologies, data sources, or perspectives in order to cross-verify results and enhance the validity of findings. By employing different research methods, such as surveys, interviews, and observations, researchers can gather a more comprehensive understanding of the phenomenon being studied. This approach helps to mitigate biases that may arise from relying on a single method, thus leading to more robust and trustworthy conclusions. When employing data triangulation, the diverse evidence collected can either support or challenge the findings from one source, offering a more nuanced and well-rounded perspective on the research question. This technique is particularly valuable in sociology, where human behavior and social contexts can be complex and multifaceted. In contrast, using a single source of data limits the researcher’s ability to capture the complete picture and may introduce significant bias. Analyzing only quantitative data or focusing solely on qualitative interviews also restricts the depth and breadth of understanding that can be achieved through triangulation.

Data triangulation in research refers to the practice of combining multiple methodologies, data sources, or perspectives in order to cross-verify results and enhance the validity of findings. By employing different research methods, such as surveys, interviews, and observations, researchers can gather a more comprehensive understanding of the phenomenon being studied. This approach helps to mitigate biases that may arise from relying on a single method, thus leading to more robust and trustworthy conclusions.

When employing data triangulation, the diverse evidence collected can either support or challenge the findings from one source, offering a more nuanced and well-rounded perspective on the research question. This technique is particularly valuable in sociology, where human behavior and social contexts can be complex and multifaceted.

In contrast, using a single source of data limits the researcher’s ability to capture the complete picture and may introduce significant bias. Analyzing only quantitative data or focusing solely on qualitative interviews also restricts the depth and breadth of understanding that can be achieved through triangulation.