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STUDYING BEHAVIOR © 2009 The McGraw-Hill Companies, Inc.
Define variable and describe the four categories of variables: situational, response, participant, and mediating variables Define operational definition of a variable Describe the different relationships between variables: positive, negative, curvilinear, and no relationship © 2009 The McGraw-Hill Companies, Inc.
Compare and contrast nonexperimental and experimental research methods Distinguish between an independent variable and a dependent variable Discuss the three elements for inferring causation: temporal order, covariation of cause and effect, and elimination of alternative explanations © 2009 The McGraw-Hill Companies, Inc.
Discuss the limitations of laboratory experiments and the advantage of using multiple methods of research Distinguish between construct validity, internal validity, and external validity © 2009 The McGraw-Hill Companies, Inc.
Four General Categories Situational variables Response variables Participant or subject variables Mediating variables © 2009 The McGraw-Hill Companies, Inc.
Variable is an abstract concept that must be translated into concrete forms of observation or manipulation Studied empirically Help communicate ideas to others © 2009 The McGraw-Hill Companies, Inc.
Positive Linear Relationship Increases in one variable relate to increases in another Negative Linear Relationship Increases in one variable relative to decreases in another Curvilinear Relationship Increases in one variable relative to both increases and decreases in another No Relationship Correlation coefficient Relationships and Reduction of Uncertainty © 2009 The McGraw-Hill Companies, Inc.
Nonexperimental Method Direction of Cause and Effect The Third-Variable or Confounding Variable Problem Experimental Method Experimental Control Randomization © 2009 The McGraw-Hill Companies, Inc.
The casual possibilities in a non-experimental study © 2009 The McGraw-Hill Companies, Inc.
COMPARISON OF NON-EXPERIMENTAL AND EXPERIMENTAL METHODS DESCRIPTIONEXAMPLESADVANTAGESDISADVANTAGES NON- EXPERIMENTAL Relationships studied by making observations or measuring variables as they exist naturally Behavior observed as it naturally occurs Asking people to describe behavior Directly observing behavior Recording physiological responses Examining public records Allows measure of covariation between variables IV can be observed in a natural context Allows us to study participant variables that cannot be manipulated Difficult to infer cause and effect Direction and third variable problem Difficult to control many aspects of the situation EXPERIMENTAL Direct manipulation and control of variables, then response or result is observed Measuring behavior then introducing a manipulation and measuring an outcome Random assignment of participants, experimental group experiences manipulation, control group does not, outcome variable is measured Reduces ambiguity in interpretation of results regarding cause and effect Attempts to eliminate the impact of all possible confounding third variables Permits greater experimental control Reduces the possible influence of extraneous variables through randomization High control may create an artificial atmosphere Can be unethical or impractical © 2009 The McGraw-Hill Companies, Inc.
Independent = Cause Dependent = Effect Dependent variable y-axis Independent variable x-axis © 2009 The McGraw-Hill Companies, Inc.
Inferences of Cause and Effect Require Three Elements: 1. Temporal precedence 2. Covariation between the two variables 3. Need to eliminate plausible alternative explanations © 2009 The McGraw-Hill Companies, Inc.
Artificiality of Experiments Ethical and Practical Considerations Participant Variables Description of Behavior Successful Predictions of Future Behavior Advantages of Multiple Methods © 2009 The McGraw-Hill Companies, Inc.
Construct Validity Adequacy of the operational definition of variables Internal Validity Ability to draw conclusions about causal relationships from our data © 2009 The McGraw-Hill Companies, Inc.
External Validity Extent to which the results can be generalized to other populations and settings Conclusion Validity Draws reasonable conclusions based upon an analysis of the data © 2009 The McGraw-Hill Companies, Inc.
Critically Evaluating Research Construct ValidityInternal ValidityExternal Validity Evaluate the adequacy of the operational definition. Is the operational definition sufficiently measuring the construct it claims to measure? Evaluate the extent that it was the independent variable that caused the changes or differences in the dependent variable. Are there alternative explanations (confounds )? Evaluate the extent that the results can generalize to other populations and settings. Can the results be replicated with other participants? Can the results be replicated in other settings? Conclusion Validity Do statistics support the claim? © 2009 The McGraw-Hill Companies, Inc.
FUNDAMENTAL RESEARCH ISSUES © 2012 The McGraw-Hill Companies, Inc.
Research System Theory Hypotheses Data Verification Theory building Hypothesis generation Measurement issues Research design Sampling issues Statistical.
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