Qualitative data analysis refers to one form of systematic analysis of data for the purpose of increasing knowledge and understanding of a theme, topic, or question. The types of data that correspond to this approach to research can include numbers, but also include written, spoken, acted or illustrative works, thoughts, ideas, phrases, and observations. These ‘holistic’ forms of data are compiled using techniques such as interviews, video and sound recording, and graphical representations, and can include written works such as newspaper and journal articles, books, poems, and any other medium that can be objectively observed and analyzed. Virtually anything that is expressed through some medium can be analyzed using qualitative methods.
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The goals, process, methods, and outcomes of qualitative data analysis are both similar and dissimilar to those of its sister approach, quantitative data analysis. In quantitative data analysis, numerical information, such as counts and percentages, are processed, usually using some type of software, such as the Statistical Package for the Social Sciences (SPSS)or the Statistical Analysis System (SAS), in order to produce a numerical relationship or description, which is used to answer a question or test a hypothesis, often basing such conclusions on notions of statistical probability. In qualitative data analysis, while the goal is typically to answer a question or questions as well, the type of answer that is sought can be quite different, as can the methods used to address the question.
First off, quantitative data analysis usually aims to test a hypothesis using a deductive approach to data collection and analysis. A deductive approach starts with something broad, like a theory, and proceeds to collect and test data to form a conclusion about a specific aspect of topic that is informed by theory and previous research. This approach starts with the general and proceeds to the specific. Qualitative data analysis, on the other hand, is an approach that typically follows the path of inductive reasoning, which in many ways is the inverse of the deductive path. An inductive approach begins with something specific, like a certain group of people that the researcher wants to learn more about, and then proceeds to collect and analyze data to form more general conclusions about the subject or subjects. In this approach, the object of the investigation is chosen first, which is then analyzed to discover or illustrate specific attributes and characteristics.
Although qualitative analytical methods deal with non-numerical data, they often utilize software programs to quantify and interpret the qualitative data. One of the most popular of these programs is QSR International’s NVivo software. This program enables researchers to conduct a wide variety of procedures on unstructured data, such as classification, sorting, and creation of various arrangements of the data in order to examine relationships by conducting queries, linking, utilizing search tools, and model creation.
Analytic induction is another method for analyzing qualitative data. In this method, the analyst develops a hypothetical statement of an event, scenario, or theme. The analyst then proceeds to pine through the data looking for situations that either fit or discredit the working hypothesis. Each time an observation is encountered that runs contrary to the hypothesis, the hypothesis is revised so that it eventually encompasses all the observations.
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