Correlations

• Correlations investigate the relationship between co-variables.
• Correlations cannot infer cause and effect.
• Correlations are shown on scattergrams, which plot one variable against another.
• Positive correlations suggest that as one variable increases so does the other.
• Negative correlations suggest that as one variable increases, the other decreases.
• Some correlations can show no relationship between the two variables.
• Correlations collect quantitative data, allowing for numerical analyse.
• Correlations only show the relationship or association, they do not tell us what is causing it.
• Correlations are measured using Spearman’s Rho or Pearson correlation coefficient analysis.
• A correlation coefficient can be anywhere on the continuum from -1 to +1. The closer to the value of 1, the stronger the correlation.
• A weak correlation would have a coefficient closer to the value zero.
• Correlations can tell you the strength and type of the relationship between two or more variables.
• Spearman's Rho is a non-parametric test of correlation that assesses the strength and direction of the relationship between two variables, while Pearson correlation coefficient is a parametric test.
• Limitations of correlations include the inability to establish causation, the potential for confounding variables, and the reliance on the strength and direction of the relationship.
• The range of values for a correlation coefficient is -1 to +1.
• Ways to determine the strength of a correlation can be by calculating the correlation coefficient and examining the spread of scores away from the line of best fit on the scattergram.
• The type of correlation can be seen on the scattergram by looking at the direction of the line of best fit.