Correlations

    AQA
    A-Level

    Correlational analysis is a non-experimental technique used to measure the strength and direction of the relationship between two or more co-variables. Unlike experimental methods, there is no manipulation of an Independent Variable (IV), meaning causal conclusions cannot be drawn. Candidates must demonstrate mastery in interpreting correlation coefficients (Pearson’s r or Spearman’s rho) ranging from -1.0 to +1.0, constructing and analysing scattergrams, and evaluating the utility of correlations in preliminary research. Critical understanding of the 'third variable problem' and the distinction between linear and curvilinear relationships (e.g., Yerkes-Dodson) is essential for top-band marks.

    0
    Objectives
    4
    Exam Tips
    4
    Pitfalls
    3
    Key Terms
    4
    Mark Points

    What You Need to Demonstrate

    Key skills and knowledge for this topic

    • Credit clear identification and operationalisation of co-variables, rejecting any reference to IV/DV
    • Award marks for accurate interpretation of correlation coefficients regarding both strength (number) and direction (sign)
    • Credit explanation of the 'third variable problem' when evaluating validity
    • Award marks for scattergrams that feature continuous scales on both axes and accurate plotting of data points

    Example Examiner Feedback

    Real feedback patterns examiners use when marking

    • "You have correctly identified the direction, but failed to comment on the strength of the coefficient"
    • "Replace 'IV and DV' with 'co-variables' immediately to access marks in this section"
    • "Your scattergram lacks labelled axes; ensure units of measurement are included"
    • "You asserted causation; modify your argument to suggest a relationship and consider intervening variables"

    Marking Points

    Key points examiners look for in your answers

    • Credit clear identification and operationalisation of co-variables, rejecting any reference to IV/DV
    • Award marks for accurate interpretation of correlation coefficients regarding both strength (number) and direction (sign)
    • Credit explanation of the 'third variable problem' when evaluating validity
    • Award marks for scattergrams that feature continuous scales on both axes and accurate plotting of data points

    Examiner Tips

    Expert advice for maximising your marks

    • 💡When designing a study, explicitly state how co-variables are measured (e.g., 'score on a stress scale' not just 'stress')
    • 💡For 'Evaluate' questions, use the 'Third Variable Problem' to critique the internal validity of the findings
    • 💡Check the sign (-/+) for direction and the number (0.0-1.0) for strength independently before writing your conclusion
    • 💡Ensure hypotheses are clearly non-experimental; use 'relationship between' rather than 'difference between'

    Common Mistakes

    Pitfalls to avoid in your exam answers

    • Referring to 'Independent Variable' and 'Dependent Variable' instead of 'co-variables'
    • Concluding cause-and-effect relationships solely based on a strong correlation coefficient
    • Drawing a line of best fit on a scattergram when not explicitly requested by the question
    • Confusing a 'negative correlation' (inverse relationship) with 'no correlation' (zero relationship)

    Key Terminology

    Essential terms to know

    Likely Command Words

    How questions on this topic are typically asked

    Design
    Calculate
    Explain
    Discuss
    Evaluate
    Interpret

    Ready to test yourself?

    Practice questions tailored to this topic