COMM 88 Lecture Notes - Lecture 5: Dependent And Independent Variables, Internal Validity, Cortisol
Comm 88 Lecture 5
April 17, 2018
Types of Relationships Between Variables
•Causal relationships between variables
•X influences/affects/changes Y
•Ex: Violent TV viewing produces aggressive behavior
•Cause has to come first
Different Methods for Testing Different Relationships
•Survey/observational research (Researcher A)
•Tests associations (just relationships/correlations)
•Measures/observes some attitudes/behaviors and correlate them OR compare existing
groups of people on some measure
•Great for external validity
•Ability to generalize results to other people (IF use representative sample) and to “normal
life” settings (IF observe or ask people about normal behavior, etc.)
•Poor for causality!
•Experimental research (Researcher B)
•Tests causal connections
•Manipulate variables
•Separate people into groups, give different “treatment” to each group, control everything
else, measure effects (usually on attitude or behavior)
•Great for internal validity - ability to establish that X causes Y
•Not just connection between variables, but also establishes time order (which variable
came 1st) and rules out “extraneous” (3rd) variables.causes
•Poor for generalizability!
Defining Concepts and Variables
•Independent variable (IV)
•In experiments:
•A “causal” variable (the cause in a cause/effect relationship)
•Manipulated by a researcher
•A “predictor” variable (“predict” does NOT mean “cause”!)
•Dependent variable (DV)
•In experiments:
•An “effect” or outcome
•The variable affected/changed by the IV
•In survey/observational studies:
•A variable being predicted by the IV (sometimes called “criterion” variable)
•Could the IVs/DVs be other way round in this surve? YES, prediction predicts identity
(same relationship)
•Conceptualizing your variables - defining what the concepts mean for purposes of
investigation
•Usually based on theory/prior research
•Example variable “fear”: What is it?
•Conceptual definition
•Operationalizing your variables - deciding exactly how the concepts will be measured (or
manipulated) in a study
