If you’ve ever constructed a survey, you’ve probably given some thought to whether you’re trying to gather qualitative or quantitative information — or perhaps both. Is there something that makes quantitative information superior to qualitative? This entry discusses the differences between the two, also suggesting that qualitative answers can also be coded quantitatively.

Quantitative Research

A scientifically calculated sample from a population is asked a set of questions on a survey to determine the frequency of responses. The sample size for a survey is determined by using formulas to suggest the sample size necessary to generate acceptable findings.

Generally, researchers would like sample sizes that yield findings with at least a 95% confidence level and a plus/minus 5 percentage points margin of error.

Qualitative Research

Qualitative Research is much different and more subjective than quantitative research. Information that is qualitative is mainly collected in individual, in-depth interviews and focus groups. This type of research is exploratory and open-ended. Small numbers of people are interviewed and/or a relatively small number of focus groups are conducted.

Participants are asked to respond to general questions, and the interviewer or group moderator probes and explores their responses and to determine the degree of agreement that exists in the group. The quality of the findings from qualitative research is directly dependent upon the skill, experience and sensitivity of the interviewer or group moderator. This type of research is often less costly than surveys and extremely effective in acquiring information about peoples’ communication needs and their responses to and views. It is the preferred method of choice in instances where quantitative measurement is not required.

Coding Qualitative Data

Sometimes there is a thought that quantitative data somehow is superior to qualitative data; however, all qualitative data can be coded quantitatively. Anything that is qualitative can be assigned a meaningful numerical value. These values can then be manipulated to help achieve greater insight into the meaning of the data. For example, consider the open-ended question “Please add any additional comments.” The immediate responses are text-based and qualitative that could be classified based on the type of responses. For example, the responses could be sorted into simple categories, giving the category a short label that represents the theme in the response, such as:

Quantitative Qualitative
*sample size is large *sample size is small
*Objective *Subjective
*Questions are stated and subjected to empirical testing to verify them *Dialectical and interpretive
*Focuses on phenomenal that can be explained by numbers and stats *Does not depend on the use of numbers or measurements
*Tries to establish causal relationships *Generates hunches
*Needs a set plan for the completion of research *Is very flexible and changes as the data and circumstances change
*Degree of replicability is high *Degree of replicability is low

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