Correlational Studies

    Cards (2)

    • Correlational Studies
      • Analyses co-variables relationship
      • Cause + effect inferred
      • Observations or self-report data to generate ordinal data
      • only one does
      • RMD
      • Spearman RHO
      • Identifies 4 correlation types: positive (direct proportion), negative (inverse), curvilinear + zero
      • Correlation coefficient displays correlations' strength/direction on scatter graph (+1 to -1)
      • 3 Interpretations: cause + effect, 3rd variable (other cause), or chance (not related)
      • Natural variables, little manipulation; less contrived, more valid + realistic
      • Investigate situations experiment can't; indicate strength + relationship type
      • Indicate relationship, not cause + effect, less valuable
      • At least 1 measured variable has to be operationalised; artificial + contrived, may obscure other factors (validity issue)
    • Correlational Studies Evaluation
      Strengths:
      • Little variable manipulation
      • Occur naturally
      • Measured from existing situations
      • Less contrived
      • Less control is needed
      • More valid and realistic
      • Allow researchers to investigate situations that experiment can't
      • Also indicate the strength and type of relationship
      Weakness:
      • Indicate relationship, not cause and effect
      • Scientific knowledge needs causal connections
      • Cause is more valuable
      • Validity issues
      • At least one measured variable has to be operationalised
      • Often quite artificial and contrived
      • May obscure other factors
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