What is a data triangulation?
Data triangulation is the use of a variety of data sources, including time, space and persons, in a study. Findings can be corroborated and any weaknesses in the data can be compensated for by the strengths of other data, thereby increasing the validity and reli- ability of the results.
What is triangulation of data in research?
Triangulation refers to the use of multiple methods or data sources in qualitative research to develop a comprehensive understanding of phenomena (Patton, 1999). Triangulation also has been viewed as a qualitative research strategy to test validity through the convergence of information from different sources.
Which is the best example of triangulation in data?
Answer» d. Collecting data from users in different ways with different methods.
Why is data triangulation important?
Triangulation facilitates validation of data through cross verification from more than two sources. It tests the consistency of findings obtained through different instruments and increases the chance to control, or at least assess, some of the threats or multiple causes influencing our results.
What is the process of triangulation?
Triangulation is a surveying method that measures the angles in a triangle formed by three survey control points. Using trigonometry and the measured length of just one side, the other distances in the triangle are calculated.
What are the advantages of using triangulation in research?
Triangulation can help: Reduce bias that comes from using a single method, theory, or investigator. Enhance validity by approaching the same topic with different tools. Establish credibility by giving you a complete picture of the research problem.
What is investigator triangulation in qualitative research?
Data triangulation in qualitative research uses different data sources, persons, time, and space in a study to increase the validity of the results. The investigator triangulation involves using several investigators, evaluators, observers, researchers, or data analysts in a study.
What does data triangulation mean?
What does data triangulation mean? Data triangulation is where the researcher uses two or more methods for the verification of the findings and results. Data triangulation is also called cross examination because it double or even triple checks the results obtained from the research. The basic idea behind this or the rationale for using this
What are the three types of triangulation?
Researchers look for three types of triangulation: convergence, complementarity, and divergence. Convergence indicates there is a strong degree of overlap and accuracy between the data sets collected using different methods.
What is the difference between credibility and triangulation?
Credibility is about how confident you can be that your findings reflect reality. The more your data converge, or or agree with each other, the more credible your results will be. Triangulation helps you get a more complete understanding of your research problem.