Correlation

• Association


  Relationship between two co-variables
• Scattergram


  Illustrates the strength and direction of an association between two co-variables
• Types of correlation


  • Positive correlation - co-variables rise or fall together
  • Negative correlation - one co-variable rises and the other falls
  • Zero correlation - no relationship between the two variables
• Positive correlation


  • Number of caffeine drinks
  • Anxiety level
• Negative correlation


  • Anxiety level
• Zero correlation


  • Anxiety level
• Differences between correlations and experiments

  • In an experiment the researcher manipulates the IV and records the effect on the DV. In a correlation there is no manipulation of variables and so cause and effect cannot be demonstrated
  • In a correlation the influence of EVs is not controlled, so it may be that a third 'untested' variable is causing the relationship between the co-variables (called an intervening variable)
• Advantages of correlations


  • Useful starting point for research
  • By assessing the strength and direction of a relationship, correlations provide a precise measure of how two variables are related
  • If variables are strongly related it may suggest hypotheses for future research
  • Relatively economical
  • Less time-consuming than experiments
• Limitations of correlations


  • No cause and effect
  • Correlations are often presented as causal, e.g. by the media, when they only show how two variables are related
  • There may be intervening variables that explain the relationship
  • Method used to measure variables may be flawed