Definition Correlation is a statistical technique used to quantify the strength of relationship between two variables. Used a lot in psychology investigations, for example Murstein (1972) carried out a correlation analysis of ratings of attractiveness in partners ('computer dance' study). Strengths and weaknesses of correlation Strengths: Weaknesses Calculating the strength of a relationship between variables. Cannot assume cause and effect, strong correlation between variables may be misleading. Useful as a pointer for further, more detailed research. Lack of correlation may not mean there is no relationship, it could be non-linear. Analysis of correlation For a correlational study, the data can be plotted as points on a scattergraph. A line of best fit is then drawn through the points to show the trend of the data. If both variables increase together, this is a positive correlation. If one variable increases as other decreases this is a negative correlation. If no line of best fit can be drawn, there is no correlation. Correlation can be quantified by using a correlation coefficient - a mathematical measure of the degree of relatedness between sets of data. Once calculated, a correlation coefficient will have a value from -1 to +1. +1 = perfect positive correlation all points on straight line, as x increases y increases. A value close to one indicates a strong positive correlation. 0 = no correlation points show differing degrees of correlation. Note: A correlation around zero may disguise a non-linear relationship. -1 = perfect negative correlation all points on straight line, as x increases y decreases. A value close to -1 indicates a strong negative relationship. Note: In real life human situations, or psychology experiments you will not find perfect correlation between variables, life is just like that. What psychologists do is calculate a correlation coefficient, then, using statistical tables (thought up by brilliant mathematicians) work out the probability that their results could have occurred at random. If they can say there is a 95% chance of their results really showing a strong correlation, then they accept that there is one.