Research Design

Whether qualitative or quantitative in nature, I design research to answer specific social questions. When a company wants to know “how,” I design interviews, surveys, and participant-observation studies that allows us to ultimately code and analyze narratives and experiences. Qualitative methods are useful for understanding specific behaviors and finding nuances that would escape broad quantitative research and it’s especially helpful for niche issues. 

Quantitative data helps me answer specific questions about larger trends and changes in trends. Quantitative methods can be used for a small or large population, but for the results to be more reliable, we need a large sample. If a company wants to understand statistically what is happening or what will probably happen, I design surveys or analyze data that is already available through university or government data sets, or by using data a company has already collected. 

Because I have a background in both qualitative and quantitative analysis, I almost always design research to include at least a little of both methods so that we can understand even more than we initially set out to understand.

Research design is never, or almost never, done in a vacuum. Design includes multiple viewpoints and clear communication within a team.

Data Analysis

Using qualitative or quantitative research methods, I identify and interpret patterns and trends. Based upon a business’ needs, I make recommendations, such as how they can improve data collection methods for future studies, how they can improve their business model to respond to changing consumer trends, or how they should present evidence to policy makers when advocating change.

Predictive Modeling

I have a solid understanding and working knowledge of statistical modeling techniques such as linear regression, logistic regression, generalized linear models, and cluster analysis to identify and predict trends in data.

Grounded Theory

Continuously turning the kaleidoscope on qualitative data, I code and re-code until I connect nuances and identify relationships between two seemingly unrelated phenomena. This process of creating grounded theory is my favorite research method because it requires intense micro analysis of the human condition. It’s also the most time consuming practice, so it is often ignored by businesses seeking quick formulaic answers and insights.

For businesses, creating grounded theory by analyzing qualitative data serves to greatly improve customer experience, inform marketing plans, boost customer loyalty, and build brands. 

I would encourage businesses to not overlook grounded theory. Even if the full process of grounded theory is not carried out, the processes of analyzing qualitative data should not be ignored. 

Public Policy

I am passionate about progress and making change that helps create a healthier society. I create and use original data driven evidence to support arguments for policy changes and raise social awareness about issues. 

The policy issues I care about most are 

  • changing the trajectory of domestic violence through education (most of my research is focused on domestic violence issues), 
  • legalization of all entheogens for research and personal consumption, 
  • keeping our oceans and earth clean, 
  • technology advancement, and 
  • anything that improves the mental health of anyone and everyone.

Academic, Legal, & Policy Writing

I spent more than 10 years writing legal arguments and rebuttal arguments. I am an expert at summarizing data, supporting claims with evidence, and clearly articulating what actions I want decision makers to take. This experience translates well in helping businesses argue for policy change or communicate clearly on all fronts.

Thanks to my role as a teacher’s assistant at UCI and writing theses for three different disciplines, I am fluent in CMOS and AP writing styles, and I am skilled at properly citing case law. Therefore, I am able to adapt my citation and writing style according to the intended audience. My writing on the Flesch Reading Ease scale averages 30-40, which is considered difficult to read and most suitable for university graduates.

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