CRIM 321 Lecture 9: 321 lec 9
21 Mar 2016
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Techniques data analysis: must be true to data, based on understanding complexity, detail, and context of data. Use data to support: engage in process. Atend to typically hidden or unexamined stages of research process: provide beter understanding of poliical & social context of producion of knowledge. Idenifying key factors in the study and the relaionships between them: interpretaion. Transcend factual data and cauious analysis (the above) How to analyze: quesions to ask when analyzing. Need to have suicient ime for looking at data and persistent observaion. How can you know that your interpretaion is the right one: keep data/interpretaion trustworthy. General knowledge about context of data and place it in larger arena: theoreical understanding, descripive codes. Idenifying percepion, interpretaion, acion in data: literal codes. I don"t care how people see me = idgaf : analyical codes. What"s most important is how i feel about myself = internal self-assessment : focused coding.
