CRIM 321 Lecture Notes - Lecture 9: Data Analysis, External Auditor, Thick Description

• School: Simon Fraser University
• Department: Criminology
• Course: CRIM 321
• Professor: Sheri Fabian

Document Summary

Mar 12 data coding & analysis part 2. Based on understanding complexity, detail, and context of data: use data to support. Engage in process: deliberation & reflexivity, deliberately seek negative cases, atte(cid:374)d to t(cid:455)pi(cid:272)all(cid:455) (cid:862)hidde(cid:374)(cid:863) or u(cid:374)e(cid:454)a(cid:373)i(cid:374)ed stages of resear(cid:272)h pro(cid:272)ess. Provide better understanding of political & social contexts of production of knowledge. Identifying key factors in the study and the relationships between them. Interpretation: transcend factual data and cautious analysis (the above steps, pro(cid:271)e (cid:449)hat (cid:272)a(cid:374) (cid:862)(cid:271)e (cid:373)ade(cid:863) fro(cid:373)/of data. Keep data/interpretation trustworthy: understand & acknowledge data limitations (what influence and affect your data, acknowledge the limitations) Self understanding (summarize and reduce the data, categorize and give it label, condense it) Theoretical understanding (broader literature/and what you found on the research of this area) Types of data coding (categories names what you call your findings) Coding assign words to segments of text sort coded text segments condense data into analyzable segments focus on generating analytical concepts (sub codes)