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Research Methodology and Methods of Social Inquiry GSSR October 11 2010 Research Design I PowerPoint Presentation
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Research Methodology and Methods of Social Inquiry GSSR October 11 2010 Research Design I

Research Methodology and Methods of Social Inquiry GSSR October 11 2010 Research Design I

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Research Methodology and Methods of Social Inquiry GSSR October 11 2010 Research Design I

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  1. Research Methodology and Methods of Social Inquiry GSSR October 11 2010 Research Design I

  2. Research Design Research design: plan that shows, through the discussion of the causal model (theoretical) and the data, how we expect to make inferences.

  3. Stages of Social Research FORMULATION OF RESEARCH PROBLEM & THEORETICAL MODEL Chose variables and specify hypothesis PREPARATION OF RESEARCH DESIGN Define population and select sample. Develop instruments MEASUREMENT SAMPLING DATA COLLECTION DATA ORGANIZATION AND PROCESSING ANALYSES AND INTERPRETATION Make decisions about the fit of data and theory. Results are communicated to an audience. (Confirm or reject your initial theory)

  4. Formulation of Theoretical Model & Research Problem • Choosing the research question - researchable; ‘What ?’ questions; ‘Why ?” questions - interesting; no-surprize; „so what ?” • Theory • Comprehensive literature review

  5. What do these help achieve? A. Whom do we study? (units of observation) B. Which characteristics of these units do we study? (Variables) C. What are our hypotheses? (i.e. the expected relationships btw. the variables) D. Understand (better) the results; interpretation.

  6. Units of Observation (i.e. units of analysis; cases) - individuals (micro-level); households; families; groups; - networks, organizations (meso-level); - cities; states/counties; countries; regions (macro-level) Aggregate Data - Data gathered at one set of units (ex. the individual) that is combined (i.e. expressed in a summary form) to describe a larger social unit (ex. cities). Ex: Measure of city’s socioeconomic resources: average income and education of its inhabitants; \ High School performance measure: % of students who go on to college after graduation Attention: When information about individuals is aggregated to describe groups/collectivities, the unit of analysis can be either the individual or the group.

  7. Assumptions made about individuals based on aggregate data are vulnerable to the ecological fallacy (ecological inference fallacy) Error in the interpretation of statistical data: Inferences about the nature of specific individuals are based only upon aggregate statistics collected for the group to which those individuals belong. This fallacy assumes that individual members of a group have the average characteristics of the group at large. \ Ex: Aggregate data on income for a neighborhood of a city shows that the average household income for the residents of that area is $30,000. The ecological fallacy can occur if we state, based on these data, that people living in the area earn about $30,000 Examination of the neighborhood might show that it is actually composed of 2 types of residential areas, a lower socio-economic group of residents, and a higher socio-economic group. The poorer part of town residents earn on average $10,000 while the more affluent citizens can average $50,000.

  8. B. Variables = Characteristics of the units of observation A variable is a measurable characteristic that differs across observation units. Each variable assumes a set of some definite values. Units ofVariables observation Age Gender Education Political Party Case # 1 21 0 12 0 Case # 2 36 1 16 3 Case # 3 23 1 15 2 . . . . . . . . . . Case # n 33 0 17 1

  9. C. Hypotheses A hypothesis is a prediction about how variables relate to each other (i.e. the relationship btw. variables). Relationships btw. Variables: changes in the values of one variable are accompanied by systematic changes in the other variable(s). A hypothesis is usually based on theoretical expectations about how things work. At minimum, any hypothesis involves 2 variables: an independent variable (IV) and a dependent variable (DV). DV measures the presumed effect/outcome; Y IV measures the presumed cause; Controls; Intervening Variables; X Based on theory, we specify the direction of influence among variables. i.e we formulate hypotheses.

  10. Generally, social science research tests hypotheses. In statistical inference, hypotheses generally take one of the two forms: substantive and null. A substantive hypothesis represents an actual expectation about the relationship between 2 or more variables. (Ex: higher education increases the likelihood of upward mobility) To decide whether a substantive hypothesis is supported by the evidence, it is necessary to test a related hypothesis, called the null hypothesis (Ex: education has no effect on mobility.) Spurious Associations A statistically significant association between 2 variables, driven by a third variable, which affects both. Ex: positive relation (correlation) between number of firefighters at the sight of a fire, and the amount of damage produced.

  11. Social researchers test hypotheses through: - experiments - surveys - content analyses - participant observations - secondary analyses