7.1.4 Correlations

Correlation illustrates the strength and direction of an association between two or more co-variables. Plotted on a scattergram. There are positive, negative and zero correlations. In an experiment, the researcher manipulates or controls the IV to measure the effect on the DV and so is possible to infer the IV caused any change in the DV. In a correlation there is no manipulation and so it is hard to establish cause and effect. Other intervening variables of different variables could also be involved.

Strengths

Limitations

-Provides and concise and quantifiable measure of how two variables are related. Suggest ideas for possible future research if variables are strongly related to demonstrate an interesting pattern. -Correlations are often used as a starting point to assess possible patterns between variables before researchers commit to an experimental study. -Relatively quick and economical to carry out. There is no need for a controlled environment and no manipulation of variables -Less time-consuming as secondary data can be used

-Lack of experimental manipulation and control within a correlation, studies can only tell us how variables are related but not why. -Correlations cannot demonstrate cause and effect between variables therefore we do not know which co-variable is causing the other to change. May also be the case that another untested variable is causing the relationship between the two co-variables (intervening variable)