Analyzing and Interpreting Data

Mixed method methodology involves the analysis of both quantitative and qualitative data. One advantage of interpreting mixed methods data is that it offers a broader perspective on the data (Pernecky, 2016). Use of a single approach only determines the cause and effective relationship but a mixed methods design combines the strengths of both approaches thereby offering a broader viewpoint of data. 

Another advantage is that it provides a method of exploration and analysis of data 9 Muskat et al., 2012). Qualitative tools can be used to provide subtle hints that define a problem then the quantitative methods can be applied to invalidate or invalidate observations that were made (Brewer & Hunter, 2006). This avoids use of quantitative analysis as the singular tool for exploration, problem definition and development of solutions. 

The third advantage is that mixed method design usually expands the research to encompass both observation and statistical analysis, thereby making the research more comprehensive (Alasuutari, 2010). This enhances the quality of findings made especially in academia, where the mixed methods design can enhance the timelines of debates by generating more data on areas for future research and discussion (Hesse-Biber, 2010). 

Moreover, mixed methods data has certain weaknesses and the first is that it may create personal bias in interpretation of results. Pragmatic people tend to support quantitative data more than qualitative data and their personal biases may affect their objectivity. On the other hand, people with a linear thought pattern may be personally biased towards embracing qualitative results (Denzin & Lincoln, 2015). This means that depending on the personality of the individual, and the effectiveness of methodology adjustments used, then the accuracy of the research may be affected. 

The second weakness is that it may affect the validity of interpretations due to the differences in the goals of each type of research. For instance, quantitative research seeks to find a singular answer to a problem, while qualitative research is open to multiple answers to a single problem, as tools such as interviews may reveal multiple accurate answers to a single phenomenon (Babbie, 2014). Due to the inherent differences in the goals of qualitative and quantitative research, researchers who interpret data may develop invalid conclusions based on their personal preference for singular or multiple solutions to a single problem. 

References

Alasuutari, P. (2010). “The rise and relevance of qualitative research”. International Journal 

of Social Research Methodology. 13 (2): 139–55. doi:10.1080/13645570902966056

Babbie, E. (2014). The Basics of Social Research (6th ed.). Belmont, California: Wadsworth Cengage

Brewer, J., & Hunter, A. (2006). Foundations of multimethod research: Synthesizing styles. 

Thousand Oaks, CA: Sage. 

Denzin, N. K. & Lincoln, Y. S. (2015). The Sage Handbook of Qualitative Research. 

Thousand Oaks, California: SAGE Publications.

Hesse-Biber, S. (2010). “Emerging methodologies and methods practices in the field of 

mixed method research”. Qualitative Inquiry, 16(6), 415-418.

Muskat, M., Blackman, D., & Muskat, B. (2012). “Mixed methods: Combining expert 

interviews, cross-impact analysis and scenario development”. Electronic Journal of Business Research Methods, 10(1): 9–21

Pernecky, T. (2016). Epistemology and Metaphysics for Qualitative Research. London: 

SAGE Publications.