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Theory
Explains the relationship between phenomena, guides formation of hypotheses
Hypothesis
Testable statement that is derived from a theory, specifies expected relationships between varibales
Independent Variable
Variable that causes the outcome being studied, X
Dependent Variable
Variable being measured in response to changes in the independent variable, Y
Casual Mechanism
Process that links the IV to the DV
Operationalization of Variables
Process of making variables measurable and defining how to measure them, such as through surveys
EX. Likert Scale, used to measure attitudes/opinions by asking respondents to indicate level of agreement
Three different levels of data
Individual Level Data - data collected from individual respondents, used to analyze personal perceptions/behaviours
Aggregate Level Data - data collected at macro level (EX. country/year data) to analyze broader trends
Multi-Level Analysis - examining data at all levels to test hypotheses
Empirical Analysis
Evaluating data to see if it supports/contradicts a hypothesis
EX. Quantitative Empirical Methods - systematic approaches used to test hypotheses and theories through numerical data and statistical analysis
EX. Regression Analysis - Statistical method used to model the relationship between variables, often used to test hypotheses
Types of Evidence
Consistent Evidence - Empirical findings that support a hypothesis or theory, increases confidence in its validity
Inconsistent Evidence - Empirical findings that contradict a hypothesis or theory, prompting revision or rejection
Evaluation
Ongoing assessment of both theory and hypothesis based on empirical findings, leading to refinement or revision
Three Types of Quantitative Empirical Methods
Forecasting - process of making predictions about future events based on past data and trends
Description - collects information through public polling, does not control
Casual Question - Research Inquiry, trying to understand cause and effect relationship between variables