Qualitative and quantitative refers to the distinction between non numerical and numerical data
- It is possible to make qualitative data quantitative (e.g., Mary is prettier than Bertha; Mary is a 9, Bertha is a 4, if the information is available
- It is possible to make quantitative data qualitative (Harry is 6 feet tall, Fred is 5 ft. 10 in. tall; Harry is taller than Fred or Harry is tall, Fred is average)
Characteristics of qualitative data
- Tends to be in words (though nominal data is qualitative)
- Often is richer in meaning (more nuanced) than quantitative data
- More ambiguous than quantitative data (e.g., "She is older than her years.")
- Not amenable to statistical analysis so other analytic methods are employed
Qualitative Data Analysis
- Searching for patterns of similarity and dissimilarity (similarities may be norms or universals)
- in observational studies, you may watch to see if all jaywalkers first look for cops; if all churchgoers say "amen" at appropriate times, etc.
- in interviews, you may look for similar responses from informants (how do you determine what "similar" is?)
- Ways of looking for patterns
- frequencies: How often do people use park district facilities in the area? (Note that people may not be accurate in their reports.)
- magnitudes: What is the level of use; do they just walk in the park or actually use (use up) facilities? Magnitudes can be described in Boolean terms ("More people use park facilities on Saturdays than on Sundays.")
- structures: What different sorts of facilities are used; what different sorts of activities take place?
- processes: Is there any order among the elements of structures? That is, do those who use some facilities tend to use others?
- causes: Why do some people use facilities while others do not? Are there characteristics common to users/non users?
- consequences: How does the use of park facilities affect the users? The facilities?
- The search for explanations
- typically, tentative conclusions guide future observations (as in anthropological field research)
- alteration of explanations & conclusions as you proceed is not only normal, it is proper. In a survey, you are stuck with the questions that you have; not so in qualitative research.
- introspection: examining your own thoughts and feelings-taking the role of the "other"
- sometimes explanations come in the form of "interpretations," that is, what it means to be a member of a particular group, for example.
- Strengths and weaknesses of qualitative (field) research
- validity: there is opportunity to examine meanings in detail
- good for examining social processes over time
- flexibility: you can alter your methods when needed
- problem: Presumably, seeing is believing but believing might lead to seeing, so validity can be compromised.
- reliability: how is reliability to be determined? (Examples from anthropology)
- subjectivity: how can you (as the reader) evaluate the position of the researcher (his or her religious beliefs, political stance, feelings toward the research subjects, etc.)
Kinds of Qualitative Methods
- Participant-observation ("field research")
- The interview
- iterative, flexible, interactive
- Documentary/archival research
Possible contrasts between qualitative and quantitative methods
- Ideographic and nomothetic
- particular vs. general
- humanizing vs. dehumanizing (???)
- individual vs. statistical
- exhaustive vs. partial
- Emic vs. etic
- Interpretive vs. explanatory
- Emergent theory vs. theory-driven (inductive vs. deductive)
- Social constructionism vs. realism
Issues in qualitative and quantitative research
- What is the research goal?
- Reliability and validity
- Epistemology: are we (or should we) be more interested in meaning or in explanation of causes and effects?
- Natural vs. artificial setting
- Participation vs. observation (and everything in between): "going native" vs. "the Martian"
- "Objective" and "subjective"