Consider Why Coding Is Important In Qualitative Analysis

Coding Data
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For this Application Assignment, consider why coding is important in qualitative analysis. Then reflect on the differences among open, axial, and selective coding and types of data for which each would be appropriate.
Importance of coding in qualitative analysis
Coding is associated with organizing and sorting the data, where the data is labeled, compiled and organized. Coding is an important step in qualitative analysis to categorize the various variables and makes it easier to document the research when concepts are clearly coded (Bachman & Schutt, 2014). In qualitative data analysis, the process is faster when researchers use different codes as they can establish relationships between variables better when there is coding. Data is collected and coded to represent the various variables of interests in a research, and when collecting data from respondents it is advisable to utilize standardized coding instruments.
Coding makes it easier to identify and locate the data to facilitate data analysis. Organizing the data in systematic way also means that locate the researchers can locate the required material easily since the data is categorized. As such, the organized data becomes more meaningful to the researchers and the users when the data is coded. Even as the researchers may interpret the data differently depending on coding, systematic organization should be prioritized such that people can identify the emerging trend on the subject matter being studied. Coding goes beyond labeling to linking the categories to generate meanings and represent the themes.
Care should be exercised to avoid distorting the implied meaning when coding as qualitative research seeks to delve deeper in a topic area. The validity of samples chose for qualitative research is considered when sampling and before categorizing the data (Robinson, 2014). Coding of data not only improves the accuracy of data, but also enhances search since the categories are grouped depending on the attributes. The most important elements of the data are considered in the analysis, a...