Correlation

• A correlation is a statistical measurement of the relationship between two or more co-variables. • Correlation illustrates the strength and direction of an association between co-variables.
• Correlations are plotted on a scattergram: one co-variable forms the x-axis and the other the y-axis.
• Co-variables are usually represented numerically
• In correlations, there is no manipulation of the variables and therefore it is not possible to establish cause and effect between co-variables. For example, even if we found a strong positive correlation between caffeine and anxiety; it may be that people are anxious for many reasons (personality type, stressful job, up-bringing) – the influence of these other variables we cannot assume that caffeine was the cause of anxiety. These ‘other variables’ are called intervening variables
• There is a relationship between two co￾variables. • A positive correlation exists when one co￾variable increases while the other increases. • E.g caffeine and anxiety
• Negative correlation is a relationship between two variables in which one variable increases as the other decreases.
• A zero correlation suggests that the correlation statistic did not indicate a relationship between the two variables.
• The strength of a correlation is indicated by a correlational coefficient • Possible correlations range from +1 to -1 • +1 (perfect positive correlation) meaning that both variables move in the same direction together. • –1 (perfect negative correlation) meaning that as one variable goes up, the other goes down. Correlation Coefficients