Problems in Research: Quantitative & Qualitative Methods

Deciding whether to use a quantitative or qualitative research method can be a difficult task, particularly if you aren’t familiar with the problems associated with each. Quantitative research focuses on numerical, objective and repeatable data, and avoids subjectivity. Qualitative research aims to understand the problems being investigated in greater detail, and is often quite subjective. Finding out about the problems with each method can help you decide which to use, or whether to mix the two.

Many people criticize quantitative research because the researchers have very little ability to find out more detail. For example, many quantitative research methods use questionnaires as a means of finding out percentages of the population that possess certain characteristics or think certain things. Imagine if a questionnaire asks if you wished to vote for the Republicans or the Democrats in the next election. Someone answering this question may want to vote for the Green party, but not have the option available to state that. Within the confines of the quantitative study, they will have to choose between the two. This may not seem like a relevant fact, but if 10 percent of people who answered Democrat actually preferred Greens, a massive trend will be missed because of the rigid nature of the study. Qualitative research would catch this discrepancy through use of open-ended questions.

The rigid and fixed nature of quantitative research can also result in a relevant variable being missed entirely. If someone was conducting a qualitative study into the intelligence levels of children and trying to determine whether firstborn children are more intelligent than all subsequent children, they may measure children’s IQ, and then note whether they are firstborn, second, third or fourth. This may produce a result stating that, according to the statistics, firstborn children are indeed more intelligent, and each subsequent child has a lower IQ than the one before. This seems to be a relevant finding, but it overlooks the possible variable that intelligent parents have fewer children. This could mean that the first- and second-born children have relatively intelligent parents, and fifth-born children have less intelligent parents, so the conclusion of the study is misleading.

Subjectivity -- one of the hallmarks of qualitative research -- is also one of its major flaws. The subjective nature of the information that can be gleaned from such methods as interviews and case studies means that they are open to misinterpretation and observer bias. For example, if you are performing an interview to investigate whether prisoners had abusive childhoods, observer bias could occur, in that the interviewees could exaggerate the negative aspects of their childhoods for sympathy or justification. Subjectivity is also an issue when analyzing data, because in qualitative research, data must be interpreted. Researchers could unwittingly interpret the data in a way that suggests what they wish to show. This can’t be done as easily with quantitative, numerical data.

As a result of its subjective nature, its level of detail and its relatively small sample size, you cannot generalize qualitative findings to the population at large. Quantitative research can easily generalize data, because it can convert its finding into percentages and other mathematical expressions that can be extrapolated. Unfortunately, the detailed answers that qualitative research produces make them difficult to generalize to the population at large. The level of detail in each study also means that fewer people are studied, therefore making the participants a less accurate representation of the entire populace.