correlations

• correlations illustrate the strength and direction and measures the relationship or association between 2 co-variables. These are plotted on a scattergram where each axis represents one of the variables being investigated
• statistical tests of correlation produce a numerical value between -1 and +1. This value tells us the strength of the relationship between the 2 variables. The closer the coefficient if to -1 or +1, the stronger the relationship. The closer the coefficient is to 0, the weaker the relationship
• types of correlation are:

  • positive- co variables increase together
  • negative- one co variable increases while the other decreases
  • zero- no relationship between variables
• difference between correlation and experiment is that in experiments, the researcher manipulates the independent variable and records the effect on the dependent variables. In correlations, there is no manipulation of variables and so cause and effect cannot be demonstrated
• strengths of correlations:

  • useful starting point for research- by assessing the strength and direction of a relationship, correlations provide a measure of how 2 variables are related. If variables are strongly related it may suggest hypotheses for future research
  • relatively economical- unlike a lab study, there is no need for a controlled environment and can use secondary data. So correlations are less time consuming than experiments
• limitations of correlations:

  • no cause and effect- correlations are often presented as casual, for example, by the media, when they only show how 2 variables are related. This leads to false conclusions about causes of behaviour
  • intervening variables- another untested variable my explain relationship between co variables. This may also lead to false conclusions