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Notes on Research Methods in Psychology

Scientific Method

  • Observation

  • Define problem

  • Propose hypothesis

  • Gather evidence

  • Test hypothesis

  • Reject hypothesis

  • Retain hypothesis

  • Publish results

  • Theory building

Hypothesis

  • A tentative explanation of an event or relationship

  • Testable educated guess

  • It is the rewording of a question into a statement

  • Operational Definitions: Turn a theoretical question into an empirical one

Conceptual Level vs Concrete Level

  • Conceptual Level

    • Hypothesized relationship

    • Concepts

    • Frustration

    • Aggression

  • Concrete Level

    • Operational definitions

    • Interrupted finishing a puzzle

    • Aggression

    • Number of times interrupter insults interrupter

    • Observed relationship

Frustration-Aggression Example (from Conceptual/Concrete Levels)

  • Conceptual Level: Frustration relates to Aggression as a hypothesized relationship between concepts

  • Concrete Level: Measured with operational definitions such as the number of times an interrupter insults the interruptee while finishing a puzzle; observed relationship between interruption and aggression

Critical Thinking and Scientific Research

  • Questions to ask when reading or hearing about research:

    • What am I being asked to believe or accept?

    • What evidence is available to support the assertion?

    • Are there alternative ways of interpreting the evidence?

    • What additional evidence would help to evaluate the alternatives?

    • What conclusions are most reasonable?

  • Examples to illustrate

Theories and Secondary Sources

  • What is a theory?

  • What are the sources of information?

  • Primary versus secondary

Research Methods used in Psychology

  • Method: Naturalistic Observation

    • Features: Observations of human or animal behavior in the environment it typically occurs

    • Strengths: Provides descriptive data about behavior presumably uncontaminated by outside influences

    • Pitfalls: Observer bias and subject self-consciousness can distort results and can produce anthropomorphizing of animal behavior

  • Method: Case studies

    • Features: Intensive examination of the behavior and mental processes associated with a specific person or situation

    • Strengths: Provide detailed descriptive analyses of new, complex or rare phenomena

    • Pitfalls: May not provide representative picture of phenomena

  • Method: Surveys

    • Features: Standard sets of questions asked of a large number of subjects

    • Strengths: Gathers large amounts of descriptive data relatively quickly and inexpensively

    • Pitfalls: Sampling errors, poorly phrased questions, and response biases can distort results

  • Method: Correlational studies

    • Features: Non-experimental study designed to measure the degree of relationship (if any) between two or more events, measures, or variables

    • Strengths: Demonstrates existence of relationships, can lead to predictions from one variable to the other, can be used in a variety of settings

    • Pitfalls: Relationships may be coincidental, can not determine cause-effect relationships

  • Method: Experiments

    • Features: Manipulation of an independent variable and measurement of its effects on a dependent variable

    • Strengths: Can establish a cause-effect relationship between independent and dependent variables

    • Pitfalls: Confounding variables may prevent valid conclusions (but if done well, provides the strongest evidence)

Correlation: Understanding Relationships

  • The concept of correlation as a non-experimental measure of the degree of relationship between variables

  • Correlation scale (r values):

    • Perfect negative relationship: r = -1.00

    • Very large negative: r = -0.75

    • Large negative: r = -0.50

    • Moderate negative: r = -0.30

    • No relationship: r = 0.00

    • Small positive: r = +0.10

    • Moderate positive: r = +0.30

    • Large positive: r = +0.50

    • Very large positive: r = +0.75

    • Perfect positive: r = +1.00

  • Note on interpretation: Correlation does not imply causation; relationships may be coincidental

  • General interpretation framework: strength and direction of association

  • Basic formula (for reference): r = \frac{\mathrm{cov}(X,Y)}{\sigmaX \; \sigmaY}

Experiments

  • Purpose: establish a cause-effect relationship by actively manipulating an independent variable and observing effects on a dependent variable

  • Experimental design features:

    • Possible subjects

    • Experimental group

    • Random assignment (controls for subject differences)

    • Study and testing conditions

    • Identical conditions to control extraneous variables

    • Music included (in the example)

    • Control group

    • Independent variable (Cause)

    • Dependent variable (Effect)

    • Question: Is there a difference?

    • Example labeling: Behavior (test scores) as the dependent variable, Independent variable such as presence/absence of music

Quasi-experiments

  • Features: Measurement of dependent variables when independent variables were not entirely under the experimenter’s control

  • Strengths: Can provide strong evidence suggesting cause-effect relationships

  • Pitfalls: Lack of full control may weaken conclusions