wk6 case studies

A case study is an intensive and documented research project on a population, scenario, or group. They may contain qualitative and/or quantitative research. You can organize your subjects multiple ways, and are limited to the five hat racks: categorically (by similarity or relatedness) [i.e Graves], time (chronologically) [Brandt], location (position) [Hayes], alphabet, and continuum.

Data is collected and organized in many different methods. Surveys, recordings, observations, opinions, oral discourse, written discourse, and through conversations and de/briefings. If the researcher has a defined hypothesis or theory, the research trends can be compared in some way. The idea of development and code come into play during the analysis.

Generalizations can be made based on the purpose of the research. If hard evidence and trends are demanded, then a well-documented and tested study needs to be completed. Studies are usually generalized though and typically state that future research may be required. Yet, some research may be composed of many case studies to present an argument.

wk5

Blog Question: How does conducting research on the Internet impact the
ways that researchers must deal with human subjects?

Internet-based research needs to take into consideration basic human rights while conducting research. The IRB notes how Beneficence, Justice, and Respect for Persons must be upheld.

Depending on the nature of the online research, one must carefully consider if the human subjects understand the risks, are aware of the research, have consented to the research, and that respect is upheld. Gathering or publishing data that did not follow is unacceptable.

After reviewing the CITI modules online (requested by Clemson's review board), I am much more familiar with the histories of unethical research and the resulting consequences.

Wk4 - Measurement

What distinguishes qualitative from quantitative designs?

Qualitative designs are categorial; quantitative are numerical. Yet, they are both rhetorical. In terms of scale, one can adjust the perception of quantitative results, whereas this is much harder to achieve with qualitative designs. Qualitative designs are not mathematical (i.e. you cannot calculate a distance or assign a comparative 'value' to them).

What is the difference between validity and reliability? 

The classic example is the dart board. You may be able to produce reliable results (consistent) but are they actually valid for measuring what it is your researching? Result that are valid does not imply reliability (the internal and external consistency of the data), and vise-versa.  

What is meant by probability and significance?

These go hand-in-hand. the percent chance of occurrence is the probability, but it may mean little if your data is not significant. You can provide probabilities, means, deviations, etc for objects, but if they are not significantly different, your probabilities are not valid.