Correlations

• Correlations are the analysis of the relationship between co-variables.
• Scattergrams are graphs used to plot the measurement of two co-variables.
• Positive correlation - As one variable increase, the other also increase.

  Negative correlation - As one variable increases, the other decreases.

  Zero correlation - No relationship between the two co-variables.
• Correlation coefficient:

  • Represents both the strength and direction of the relationship between the co-variables as a number of -1 and +1.
  • These are calculated using either Spearman's rho or Pearson's.
  • Inter-rater and test-retest reliability is assessed in this way.
  • Correlation coefficient is equal / greater than 0.8 to show a strong correlation.
• Strengths of correlations:

  • They can highlight potential casual relationships which can then be tested with experimental methods to discover cause and effect relationships.
• Strengths of correlations:

  • Co-variable data usually already exist and is easily accessible so there is very few ethical problems in data collection.
• Strengths of correlation:

  • Correlation coefficient is often a useful tool in describing both the direction and strength of relationships between factors.
• Limitations of correlation:

  • Does not show causation. While a strong correlation may suggest a relationship exists between two variables, it does not show which variable led to the change. There is also a possibility that a third unknown variable caused a change in both co-variables.