A500.7.3.RB_Quantitative Research Reflection

             MLSD 500: Leadership Found in Research

     A500.7.3RB – Qualitative Research Reflection

Submitted to ERAU Worldwide

in Partial Fulfillment of the Requirements of the Degree of MBAA

Embry-Riddle Aeronautical University

Worldwide

Online Campus

September 24, 2015

         

Social researchers believe that patterns and regularities occur in society and that these are not simply random events. Patterns necessitate interest in the formulation of explanations. These explanations are presented in theories that allow us to come to a sense of reality. On the basis of theory, we can develop hypotheses about relationships that ought to exist, if the theory is valid (Mamia, 2015).

Empirical research is the study of an aspect of reality. Research data is obtained by asystematic method of empirical observation. Theoretical research studies problems related to theories of a discipline. Research data consists of previous research. Scientific research is a dialogue between theory and empirical. Most research involves both theoretical and empirical element (Mamia, 2015).

Qualitative research aims at understanding. It answers primarily to “how” questions, i.e. How does this work? Meanwhile, an explanation is the goal of quantitative research, which primarily addresses “why” questions, i.e. Why does this work? Both qualitative and quantitative research can aim for a description of social reality (Mamia, 2015).

The quantitative method is based on the idea that social phenomena can be quantified, measured and expressed numerically. The information about a social phenomenon is expressed in numeric terms that can be analyzed by statistical methods. The observations can be directly numeric information, or they can be classified into numeric variables. Observations are transformed into a data matrix in which each observation unit occupies one row and each variable one column. The data matrix is the starting point for the analysis. The quantitative method enables the research and description of social structures and processes that are not directly observable (Mamia, 2015).

I have enjoyed collecting data, analyzing the results and trending the figures. I now understand how easy it is to be misled by incomplete or manipulated data and the value of random sampling to minimize risk. In a random sample, the risk of sampling error can be statistically estimated. With random sample, there is a definite level of confidence (Mamia, 2015).  Prior to this understanding, I had, no doubt, come to conclusions based on information that had not been properly vetted for balanced, unbiased input. My new understanding of the research process for data collection has brought clarity to the importance of unbiased data in quantifying conclusions, particularly as it relates to business decisions.

Reference:

Mamia, Tero. (2015). Quantitative Research Methods. General Studies/ISS. Retrieved from Microsoft PowerPoint Presentation. 

A500.6.3RB_QualitativeResearch

MLSD 500: Leadership Found in Research

     A500.6.3RB – Qualitative Research

Submitted to ERAU Worldwide

in Partial Fulfillment of the Requirements of the Degree of MBAA

Embry-Riddle Aeronautical University

Worldwide

Online Campus

September 13, 2015

         

Comparing and Contrasting, Qualitative and Quantitative Measures

They say that it’s not about the quantity of friends but the quality. But when qualitative and quantitative data is applied in a statistical sense, quantitative data has the distinction of being information pertaining to measurable numbers, whereas qualitative data, is data that is unable to be measured, like feelings, senses, and opinions.

I would like to clarify that I am a quantitative gal, who prefers data that is factual and logical, preferred to opinion or interpretation. However, this blog concludes that both qualitative and quantitative methods are important to management problem solving and related to the purpose of analysis (Wostenholme, 1999). For example, it would be more prudent to qualify an opinion, then back it up with quantifiable data.

The strengths and weaknesses of qualitative methods

There is little doubt that the methods of qualitative research provide a significant level of assistance to thinking. Qualitative method enhances linear and `laundry list' thinking. The methods bring much needed tools to the strategic areas of management and allow a wide range of managers to access the power of feedback thinking (Wostenholme, 1999).

The dangers claimed for qualitative method range from worries that it might, in the wrong hands, lead to inappropriate insights, to concerns that it will lead to fundamentally wrong inferences. One of the major criticisms of qualitative methods is the inability to become an expert and that the issue is rarely explained by its proponents (Wostenholme, 1999).

Qualitative research focuses on the study of issues in depth and detail, and tends to center on how people make meaning out of their experiences. Three characteristics of qualitative methodology are: (a) a naturalistic approach, or studying real-world situations; (b) an emergent design and flexibility, or pursuing paths of discovery as they arise; and (c) purposeful sampling, where the sampling is aimed at insight about the research question, not necessarily generalizable to a population, and participants are chosen according to specific, purposeful criteria. The typical data collection methods in qualitative research (the use of interviews, long-term observations, and the use of documents or artifacts that add meaning to, or are used or created in the research context) focus on how participants make meaning of their lives individually or in social contexts (Stuckey, 2013).

The strengths and weaknesses of quantitative methods

Quantitative methods on the other hand, adds the dimension of and hence allows computer simulation to ascertain behaviors over time. It is well accepted that inferring the behavior over time of the simplest of feedback structures is very difficult even for the trained, since the human ability to consider any more than a very small number of variables at once is limited (Wostenholme, 1999).

Quantitative methods bring together the best combination of both people and their creative thinking ability and computers and their data manipulation. It facilitates the combining of soft and hard system elements, which is unique and powerful. The problem with computer simulation is that data are often not available and hence models are still speculative. One of the major problems is how to produce simple, balanced and elegant models at an appropriate level of aggregation in time and space to be useful. There is always a tendency to produce models which are too detailed and complex to sufficiently validate them against the mental models of their creators (Wostenholme, 1999).

Conclusion

The quantitative research determines what is happening on a population level, and qualitative research can be used to determine why and how that phenomenon is occurring (Stuckey, 2013). In order to solve for what, when, where, why, and the how, one must conduct both quantitative and qualitative methods, to achieve successful results.

           

However, members of research committees view qualitative research as inferior to quantitative research (Hopefl, 1997). 

There has been an increased interest in qualitative research in recent years. Qualitative research can be emotionally taxing and extraordinarily time consuming. At the same time, it can yield rich information not obtainable through statistical sampling techniques (Hopefl, 1997). 

Qualitative researchers have a special responsibility to their subjects and their readers. Since there are no statistical tests for significance in qualitative studies, the researcher bears the burden of discovering and interpreting the importance of what is observed, and of establishing a plausible connection between what is observed and the conclusions drawn in the research report. To do all of this skillfully requires a solid understanding of the research paradigm and, ideally, guided practice in the use of qualitative observation and analysis techniques (Hoepfl, 1997).

Figure I: Comparison of Quantitative & Qualitative Research

Source: Jaikumar, Maheswari, Dr. (2014). Quantitative vs. Qualitative Research: Slideshow. Retrieved from http://www.slideshare.net/maheswarijaikumar/quantitative-vs-qualitative-research

References:

Hoepfl, Marie C. (1997). Choosing Qualitative Research: A Primer for Technology Education Researchers. Journal of Technology Education. Volume 9, Number 1. Retreived from http://scholar.lib.vt.edu/ejournals/JTE/v9n1/hoepfl.html

Jaikumar, Maheswari, Dr. (2014). Quantitative vs. Qualitative Research: Slideshow. Retrieved from http://www.slideshare.net/maheswarijaikumar/quantitative-vs-qualitative-research

Stuckey, Heather. (2013). An overview of the rationale for qualitative research methods in social health: Methodologies in Social Health and Diabetes. 1, 1, 6-8. Retrieved from http://www.joshd.net/article.asp?issn=2321-0656;year=2013;volume=1;issue=1;spage=6;epage=8;aulast=Stuckey

Wostenholme, E.F. (1999). Qualitative vs Quantitative Modelling: The Evolving Balance. The Journal of the Operational Research Society. Macmillan Press. 50, 4, 422-428. DOI: 10.1057/palgrave.jors.2600700