Specification: Correlations. Analysis of the relationship between co‐variables. The difference between correlations and experiments. Analysis and interpretation of correlation, including correlation coefficients.

Correlational techniques are non‐experimental methods used to measure how strong the relationship is between two (or more) variables. In an experiment, the effect of an independent variable upon the dependent variable is measured; however, in correlational studies the movement and direction of co-variables in response to each other is measured. There is no claim of a cause and effect relationship, although after a correlational study has been conducted, further research will often be conducted to determine if one variable is in fact affecting the other.

A real‐world example of this is seen with cigarette‐smoking and lung cancer: first it was noticed that there was a positive correlation between the number of cigarettes smoked and the likelihood of developing lung cancer. Later, this research was extended and a cause and effect relationship was discovered between cigarette‐smoking and lung cancer.

There are different types of correlation:

• Positive correlation: As one variable increases the other variable increases. For example – height and shoe size.

• Negative correlation: As one variable increases the other variable decreases. For example – the GCSE grades of students and the amount of time they are absent from school.

•  Zero correlation: occurs when a correlational study finds no relationship between variables. For example – the amount of rainfall in Wales and the number of people who have read the Lord of the Rings trilogy.

Evaluation of correlational techniques

Correlational studies are an ideal place to begin preliminary research investigations. Since they measure the strength of a relationship between two (or more) variables, this can provide valuable insight for future research. This type of analysis can be used when a laboratory experiment would be unethical as the variables are not manipulated, merely correlated. In addition, secondary data can also be used in correlational studies which alleviates the concern over informed consent as the information is already in the public domain, e.g. government reports.

There are limitations associated with using the correlational method. It is not possible to establish a cause and effect relationship through correlating co‐variables. This means a researcher cannot conclude that one variable caused the other variable to increase/decrease as there could be other factors which influenced the relationship – referred to as the third variable problem. Moreover, correlations only identify linear relationships and not curvilinear. For example, the relationship between temperature and aggression is curvilinear, that is the relationship is positive to a point; however, at very high temperatures aggression declines.

Possible exam questions

1. A psychological study recorded the number of hours that children spent in a day care setting from birth to three years old, and asked each child’s primary care giver to rate their child for aggression. The study found that, as the number of hours spent in day care went up, the parents rating of aggression also went up. What type of correlation is this research indicating? (1 mark)

2. Discuss why it might be more appropriate for a researcher to use a correlation study rather than an experiment. (3 marks)

3. Outline one strength and one weakness of using correlational methods in psychological research. (4 marks)