Sociology research methods 9/16

Inductive reasoning: start with specific observations/data and derive general conclusions or theories. Data collection and analysis lead to a broader understanding.
Deductive reasoning: start from a general theory or universal principle, formulate a focused research question or hypothesis, then collect data to test it and draw specific conclusions.
Mnemonic: Inductive = observations to generalization; Deductive = theory to hypothesis to test.

Quantitative: numerical data, statistics; focuses on quantity and measurable outcomes. Often statistically backed.
Qualitative: quality/characteristics; observational, subjective; focuses on meaning, experience, and context.
Example framing helps recall: qualitative emphasizes the quality of a thing; quantitative emphasizes how many or how much.

Independent variable (IV): presumed cause or factor being tested. $IV\,.$
Dependent variable (DV): presumed effect; changes in response to the IV. $DV\,.$
Core idea: DV is dependent on IV; if IV changes, DV may change accordingly.

Primary data: original data collected for the current project (e.g., observed events, new surveys).
Secondary data: data collected for other purposes, used for new analyses (e.g., polls, census data, archives).
Examples: witnessing riots (primary) vs. library articles and previous studies (secondary).

Data analysis: process of organizing and examining data to uncover patterns and regularities; can be qualitative or quantitative.
Generalization: drawing conclusions from specific data and applying them to a broader population.
Validity: degree to which a measurement reflects the intended concept; accuracy of measurement.
Reliability: consistency of results across repeated measurements or trials.
If a finding is valid but not reliable, it may reflect accuracy but not consistency; if reliable but not valid, it may be consistent but not measuring the intended concept.

Surveys: most commonly used data collection tool.
Participant observation: researcher joins the group and observes from within.
Controlled experiments: classic treatment vs. control groups to test causality.
Content analysis: systematic examination of written/textual material to extract meaning or patterns.
Historical research: analysis of past records, archives, diaries, newspapers to understand trends over time.
Evaluation research: assesses the effectiveness of programs; often linked to evidence-based practice.

Researchers’ values can influence what problems to study, observations, and methods.
Historical ethical lapse example: the Tuskegee Syphilis Study; led to stricter codes of ethics.
Professional codes: ASA (and other fields) provide ethics guidelines.
Key requirements: informed consent, right to withdraw, confidentiality, minimization of harm, and IRB (Institutional Review Board) oversight.

Generalizations are common but can be harmful if not supported by data.
Avoid sweeping assumptions; rely on repeated studies and robust data.
Everyday generalizations (e.g., 70% of college students spend time on social media) illustrate how data inform broad claims, but context matters.

Which technique involves a researcher simultaneously participating and observing a group? Answer: $\text{Participant observation}$
What is the variable tested as the presumed cause? Answer: $\text{Independent variable}$
Which type of reasoning moves from a general theory to specific hypotheses? Answer: $\text{Deductive reasoning}$
Which type of reasoning moves from specific observations to a broader generalization? Answer: $\text{Inductive reasoning}$
Distinguish validity vs reliability:
- Validity: does the measurement reflect the concept?
- Reliability: would repeating the measurement yield the same result?