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MEDA5003 Data Visualisation And Interpretation
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MEDA5003 Data Visualisation And Interpretation
0 Download2 Pages / 297 Words
Course Code: MEDA5003
University: Curtin University
MyAssignmentHelp.com is not sponsored or endorsed by this college or university
Country: Australia
Question:
Discuss the advantages and disadvantages of interpreting mixed methods data, and give examples of the possibility of bias affecting the results in this process
Mix method designs include convergent, exploratory sequential, explanatory sequential, longitudinal mixed-methods, and multiphase iterative mix method data involves quantitative and qualitative data, etc.
Answer:
Introduction
Mixed methods data is a research methodology for conducting research which involves analyzing, integrating, and collecting qualitative and quantitative data. Qualitative data entails open-ended information which is delivered via observations, interviews, and focus groups. On the other hand, quantitative data contains close-ended data like attitudes, performance instruments, and behaviors.
Advantages
By mixing various methods of data, one is able to gain an in-depth and breadth of corroboration and understanding of the research topic. At the same time, researchers are able to offset vulnerabilities inherent in one data method. Another advantage of having mixed methods data is the possibility of triangulation that is the use of several methods of data to examine a common phenomenon. With triangulation it allows a researcher to identify other aspects of the same phenomenon more accurately by approaching it using the different data methods. Third, mixed data methods are used to corroborate or validate the results. Forth, the mixed data method is used when one data method wants to inform on another method. Fifth, one is able to look at research objectives and questions from a different angle. Also, one can use mixed data method when they want to build, elaborate or clarify on the research findings; this means that mixed data methods in explaining findings in a more better way (Marczyk, 2016).
Disadvantages
One of the disadvantages of mixed methods data is that it makes the research design more complex. Second, it is usually difficult to implement and plan mixed methods data. Third, it is usually unclear to resolve discrepancies which may arise. Lastly, the mixed method data takes more resources and time to plan (Welman, 2009).
References
Marczyk, G. D. (2016). Essentials of research design and methodology. Research methodology, pp. 121-146.
Welman, C. K. (2009). Research Design. Research methodology, pp. 35-40.
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