EMHSS699_research

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AnalyzingtheData.pdf

Analyzing the Data Analysis of quantitative data is straightforward, as long as there are no errors in the data arrays or computational errors. The biggest errors at the master's level are using the wrong statistical method or not knowing what statistical method to apply. Fortunately, there are many resources to help design the computation correctly. Within the APUS library is a series of math based videos.

Analysis of qualitative data is fraught with opportunities for error. The most common error is bias. Because words are the data element, and because any two humans will often perceive the exact same word in different ways, it's absolutely vital for the researcher to ensure that he or she is not writing their own meaning into the words that are being studied. Doing this perfectly of course is impossible, since we cannot remove ourselves totally from the observation and evaluation process. However, qualitative researchers make every effort to be conscious of the potential for bias at all times.

Qualitative analysis is largely a matter of pattern matching and looking for replication in word patterns and themes. The theory is that the more prevalent a pattern or theme is, the more likely it is to be true. Again, the possibility for error is significant. Group-think, for example, can provide a single theme answer that is absolutely wrong, and if the researcher does not realize what is happening, then the research will not be valid. A useful electronic book from the APUS library is Qualitative Research in Practice: Stories From the Field

Despite these issues, the careful researcher can ward off questions of validity and make positive contributions to knowledge and society. It just takes attention and effort.