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4 types of data gathering analysis
secondary analysis, content analysis, historical and comparative, and physical traces.
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secondary data analysis
a method of using preexisting data in a different way or to answer a different research question than intended by those who collected the data (what we did for class research papers)
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secondary data analysis sources:
Census, Labor Stats, Eurobarometer, General Social Survey
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secondary data analysis Advantages
inaccessible settings, saves time and money, avoid data collection issues, comparison with other samples, more variables and diverse sample, multiple studies combined
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Secondary data analysis Disadvantages
can’t design a study to reflect own problem/question, variables may notbe available, conceptualization/measurement/sample outside of researcher’scontrol, data quality issues such as not meeting scientific standards, bias,difference in measures and samples
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Things you should know about data when doing secondary analysis
-so know the goals of the research when it was originally done-know what was collected and what it was measuring-know the when and how it was collected, organized, and what is known about success of effort
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data:
reductions of experience
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types of data:
Qualitative and Quantitative
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data analysis
the search for patterns in data and for ideas that help explain the patterns (we did this by looking at crosstabs then connecting to theory in the final papers)
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similarities between qualitative and quantitative data analysis
: goals are the same: exploration, description, explanation; both try to understand by generalizing beyond the data to abstract/general concepts and theories—ultimate goal is to generalize to people, groups or organizations beyond those observed, both create meaning by using data to learn something more abstract and general
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differences between qualitative and quantitative data analysis
qualitative realizes abstraction and generalization are matters of degree (may not always be most important thing), qualitative focuses more on contextualizing things, qualitative emphasizes inductive reasoning (theory comes from data) instead of deductive (from theory to data), qualitative has close link between collecting data and analyzing it, qualitative has advantage of theoretical sensitivity: data collection and analysis are guided by emerging theory (since the theory isn’t something you necessarily start with)
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descriptive statistics
utilize numerical and graphical methods to look for patterns in data set, summarize the information, and present information (so frequency distribution is descriptive along with bar charts, pie charts, line graphs, etc.)
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measures of central tendency(descriptive)
(mean, median, mode)
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measures of dispersion (descriptive)
(range, standard deviation)
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measures of position(descriptive)
(z-score, quartiles, percentiles)
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inferential stats
utilize sample data to make estimates, make decisions, make other generalizations about larger set of data (here we are moving into EXPLAINING THINGS)—hypothesis testing is a part of this (cross-tabs fall under this)
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Hypothesis Testing
state assumptions of technique-level of measurement-nominal-model-independent random samples -state the hypotheses (null)-state level of significance (alpha .05) -compute the test statistic (so get Chi-Square) -determine significance (look at p) -determine strength (look at CV)-confirm direction (look at gamma, at graph, etc.) -accept or reject the null hypotheses (of no relationship)
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define code of ethics
–(participants, sponsors and users)*ethics: responsibilities researchers bear toward those who participate in research, those who sponsor it, and those who benefit from it
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4general principles in code of ethics
professional competence, integrity, professional and scientific responsibility , social responsibility, respect for peoples rights, dignity and diversity---(pick one give a summary of one of them)
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Principle E: Social ResponsibilitySociologists
are aware of their professional and scientific responsibility to the communities and societies in which they live and work. They apply and make public their knowledge in order to contribute to the public good. When undertaking research, they strive to advance the science of sociology and to serve the public good.
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modernargument vs post modern argument
the difference- expect values play to be apart of research –research is done to serve with subjects interest- involvement of subjects
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modern perspective
value neutrality, science for science sake, distance between researchers and subjects
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post-modern perspective
activism—social movements (Vietnam, racism, sexism, etc.)—post-modernists ultimately reject capitalism and model of inquiry (methods of inquiry—i.e. scientific method)—argue for new methods that are better suited to post modern (way more complicated) world—
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list theories of post modern perspectives
- -feminist theories
- -critical theory and critical race theory
- -queer theory
- -disability theory
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postmodern research is not on majority
-focus on marginalized peoples (women, people of color, lower class people, queer people, etc.)—researchers themselves more likely to be from these groups
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modernity:
15th century Europe, enlightenment/reformation were key partsof this (scientific rationality, etc.)—modernity was progressive, made promisesof liberation from ignorance and irrationality—goal was to seek generaltheories to explain life, accumulated knowledge of Western Civ,industrialization, urbanization, advanced technology, nation state, etc.—seesitself (modernity) as superior
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post-modernity
last half of 20th century, shares skepticism for pre-modernwold, questions extent to which solutions have actually produced a superiorsociety, especially for ALL of humankind (i.e. not everyonebenefitted)—modernity is not a force of liberation, but of oppression ofsubordinate groups (inequality)—questions institutional structure andinequalities and justifying role of science, rejects goals and social organizationof science
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