How to Interpret Qualitative Data

Qualitative data is "interpretative" data. The researcher must take abstract and sometimes vague data in the form of opinions, comments or observation and interpret this to create well-rounded conclusions. Unlike statistical quantitative data, information is not obvious but generally provides greater insight. For example, quantitative data may state that 70 percent of people are happy with public health care, indicating that the overall quality of public health care is good. Qualitative data, however, cannot be converted into statistics and may not "tell" the researcher that health care is good or bad until the data is analyzed. Qualitative data can provide additional information quantitative data cannot, such as the general opinion or attitude toward public health care, which aspects were good or bad and why participants had these opinions or attitudes.

Instructions

    • 1

      Understand data that has been collected. Read over written data from observations or interviews, listen to recorded interview data and try to produce an overall impression from the data. For example, a recorded interview with a working class family on the subject of health care may give the impression that health care is unequally distributed if the participants react negatively to some questions or give a negative answer.

    • 2

      Review the purpose of your study and ask what the qualitative data shows. Create a set of questions from your study's purpose, which can be brief. Focus on answers that are relevant to your study purpose, answers that reveal interesting facts, observations that relate to the study or comments that are similar to other participants.

    • 3

      Categorize data. From the basic answers created in Step 2, data could be grouped into which participants answered certain questions considered in the study. Alternatively, data can be categorized on impressions (i.e., five out of 15 participants gave a generally negative overview of public transport) or categorized by time scale (for example, dates on which the researcher observed a subject), participant groups (social class, age or gender) or qualitative methods used.

    • 4

      Look for themes and trends in the data. Consider whether a certain category of participants gave similar answers, or whether observation changed when performed again or at different times. Look for similarities between categories, contrasting opinions or facts and possible anomalous results due to study limitations.

    • 5

      Refer back to the first impressions of the qualitative data. Using the results which are now categorized, consider whether your first impressions were correct and what the data shows. If a positive response to social networking is perceived among a young category of participants and other categories, for example, the data may indicate that the younger category of participants use social networking.

Learnify Hub © www.0685.com All Rights Reserved