CCT208H5 Study Guide - Midterm Guide: Informed Consent, Univariate, Operationalization
10 Dec 2017
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Key terminology from lecture 1 to 3 including online lectures: absolute value. Causation: big data cons, big data cons (dirty, big data cons (drifting, big data cons (inaccessible, big data cons (influenced by. Representative: big data cons (often incomplete) (ie. no. of people who smoke in different countries; value of one country can vary than the other) (w7-lecture) Researcher does not have any information to identify participants (w5-lecture) Most common problem; seeing two connected things but may not be causations (w7-lecture) Missing chunks (system error), non consistent or not appropriate (w7-onlineb) Not technically easy to manage or view (w7-onlineb) People are not part of that representable population (w7-onlineb) Missing important variables (ie. demographics, behaviour in other places, useful theoretical variables) (w7-onlineb: big data cons (sensitive) Privacy, informed consent (w7-onlineb: big data (in terms of human research in the past) Experimental; have a few thousand cases, could be costly (w7-onlineb: big data (in terms of.
