Abstract
Once a research question has been established and some hypotheses have been derived, the next stage in the research process is to determine what type of data is needed to answer the question/hypotheses. There are two basic types of data in social science research: quantitative and qualitative. Quantitative data is data that represents items of interest numerically, and quantitative research involves examining patterns in such data using statistical methods. Examples of quantitative data include height measured in inches, IQ scores, years of schooling, earnings, counts of depressive symptoms, measures of attitudes, etc. Qualitative data represents small numbers of cases—situations, experiences, events—using data from observations, interviews, or archives that are usually not chosen using probabilistic methods. The phenomena investigated usually cannot be fully understood via quantification. For example, what is the process of death like for a dying person? How do caregivers deal with the death of a loved one who has suffered tremendously before death? What is it like to participate in an illegal activity like dog fighting? What is the life of street vendors in NYC like? Qualitative research involves examining responses to these types of questions interpretatively for common themes in order to understand human experience, often in marginal populations. A key distinction between quantitative and qualitative approaches is that much quantitative research is oriented toward making inferences about causal processes, while qualitative research is not.
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Notes
- 1.
Often, the focus may be on the situation or conditions in which the respondent exists, but the unit at which this is examined is the individual.
- 2.
See Exercise 5.10 and the solution; these computations constitute the basis of the hypergeometric distribution.
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Lynch, S.M. (2013). Data and Its Acquisition. In: Using Statistics in Social Research. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8573-5_3
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