Hello Everyone! I am honored to have the opportunity of continuing the LRS series staple Between a Graph and a Hard Place. Our last post began with “happy fall,” and now we are well on our way to Colorado’s mud season. Along with the change in seasons, a shift in topics feels like a great way to begin the series anew.

We left off discussing the use of observation as an important method for data collection and how to observe as unobtrusively as possible. To begin this new chapter, let’s take a step back to explore a type of research where observation is a crucial tool: qualitative analysis. 

The importance of numbers in research is impossible to overstate. While they can still be misleading, poorly displayed or simply inaccurate, we can all agree there is something reassuring about having the number data to back up your assertions. However, in a world filled with as many unique human experiences as ours, numbers alone (meaning quantitative research) can’t always give comprehensive and nuanced answers to every question, and that is where qualitative analysis shines.  

Background

In previous posts we established that qualitative analysis delves into data derived from stories and answers questions such as “why” and “how.” Now, let’s dig a little deeper. Qualitative analysis is not only a tool for stories. It is used to examine survey responses, feedback from focus groups, narratives, anecdotes, social media posts, secondary and primary sources and even artwork! In fact, practically anything that includes human expressions, perceptions, emotions, assumptions and/or experiences can be analyzed qualitatively. As muddy as this may seem at first glance, understanding the potential for qualitative analysis through multiple mediums is crucial to identifying where and how you can incorporate it into your own research.

What you might have picked up on already is that, in its broadest and most simplified sense, qualitative analysis is used to make sense of data that is not numerical. Qualitative analysis is a tool for qualitative research where language and behavior are studied to find patterns and/or anomalies that convey information about a data set.

Helpful Aspects of Qualitative Analysis

The social sciences have applied qualitative analysis to their research for over a century, but until the middle to late 20th century, qualitative data collection and analysis were thought to conflict with quantitative research methods. One reason for this is that qualitative research, as opposed to quantitative research, accepts that the researcher is never fully objective and detached from the data being examined. When analyzing language and behavior, it is important for researchers to be aware of and limit their biases by understanding and reflecting upon how their own experiences and assumptions are a lens through which the data is viewed. The researcher will be an aspect of the study in a qualitative analysis. 

The fact that qualitative analysis plays by different rules than quantitative analysis does not lessen the value of the insights that qualitative analysis uncovers. Additionally, quantitative and qualitative research do not have to be at odds with each other. These methods can work together to provide a better picture of the phenomenon under investigation. Here is an example of how qualitative analysis can bring new insights to a study:  

Let’s say a Likert scale, a quantitative tool, is used in an attempt to assess the extent to which library patrons view their library as an essential community resource. Participants in the study are asked how they feel about the statement “libraries are an essential community resource,” and one of many patrons selects the answer “strongly agree.” This is considered quantifiable because their selection of “strongly agree” counts as a tally toward the total number of participants selecting this answer. However, when the same question is asked and the same participant has the opportunity to give a narrative response they write, “I agree with this statement, but the library is also where I found my community. I met my closest friends through library programs and afterwards became involved in community outreach through them.” 

Of course, this is only one response, and a detailed qualitative analysis would include an extensive data set. However, themes such as finding community and community outreach appear in this short answer and imply that the library builds community as much as it acts as a resource for it. If this is a consistent theme through multiple participant responses, it could be crucial enough to shift the focus of the study or open up avenues to find support for the library system in the future. 

Hopefully this sheds some light on how qualitative analysis can give you insights where quantitative analysis, when used alone, might fall short. Qualitative analysis can feel subjective and potentially problematic when compared to quantitative analysis, but the important thing to remember is that the two methods exist separately as apples and oranges. In fact, the entire order of the research can be turned upside down in qualitative analysis because it is not always necessary to start with a single hypothesis that you are attempting to prove or disprove. Qualitative analysis allows for more flexibility throughout a study because you analyze data as data collection is taking place, not only at the end as is done in quantitative analysis. 

Conclusion

If you’re feeling a bit lost, or are just swamped with things to do today and need something quick to skim. Here’s a recap of five points we just covered:

  1. There are times when your research questions will not be comprehensively answered by quantitative data, let qualitative data help! 
  2. Qualitative data takes many different forms. Widening your vision of what qualifies as “data” can reveal new opportunities for learning. 
  3. There are a variety of methods for analyzing qualitative data, but whether the researcher is using their intuition or a computer software, they will never be fully removed from the research findings.
  4. Qualitative and quantitative analysis are two completely different approaches to data, viewing one through the lens of the other will only lead to frustration.
  5. Qualitative analysis allows for more flexibility to shift focus throughout the study as the data is analyzed.

These parameters for qualitative analysis will be used throughout the rest of this chapter as we begin to answer questions such as, how do you analyze this data accurately? When is it appropriate to incorporate qualitative analysis into your research? And what limitations does qualitative analysis have? I hope to explore the answers with you in future posts, and in the meantime, happy spring!