Qualitative analytical methods vary in their ability to analyze non-numerical data. Different methods are used for different types of data, such as observation, flowcharts, and grounded theory. Qualitative research differs from quantitative research in terms of data type and analysis method. Observational methods are the most common, and data can be further analyzed using other qualitative methods.
Qualitative analytical methods are diverse in their ability to analyze data and draw conclusions for non-numerical values. There are different types of qualitative analytical methods for different types of problems and data sets. For example, categorical data can be qualitatively analyzed based on patterns, themes, or other relationships. Hierarchical data can justify a qualitative approach based on the complexity of the concepts and can be further analyzed using a flowchart or diagram. The most common types of qualitative analytical methods are based on observation.
Qualitative research is often discussed in contrast to quantitative research. The difference between the two is based on the type of data and the method of analysis. If data is collected as numerical values, a quantitative approach can be employed that often accompanies statistical analysis. On the other hand, qualitative techniques are intended for data sets that generally do not lend themselves to statistical analysis. Non-numeric data can be converted to numeric values using a classification system or set of codes.
Categories can be coded and codes can be used for comparison. This do-it-yourself approach is technically referred to as the grounded theory method for benchmarking. Barney Glaser and Anselm Strauss developed it in the 1960s. The “data” is organized according to four criteria: work, relevance, adaptability and modifiability. Qualitative analytical methods like this can be used to analyze contextual data such as field or laboratory notes.
A visual representation of non-numeric data is another form of qualitative analysis. Flowcharts, infographics, and diagrams have the ability to draw reasoning and interpretation from data when it can be difficult to define relationships using another method from the list of qualitative analytical methods. A metaphorical method of analysis can also be used to understand the dataset in terms of something more recognizable. For example, the analysis of chemical processes can be explained in terms of cooking, metaphorically speaking.
Most other types of qualitative analytical methods can be summarized under the umbrella of observational methods. Whether the observation is in animal behavior, semiotics or linguistics, the power of observation can be easily applied to many scenarios. Observations can be recorded in the form of notes, sketches or photographs. The collected “data” can be further analyzed using another qualitative analytical method to classify or refine the observations. For example, frequency can be measured by counting the number of times a term is repeated in the field notes.
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