Relational Research (Correlations)

A study that investigates the connection between two or more variables is considered relational (or sometimes correlational) research. The variables that are compared are generally already present in the group of population.

In correlations it is proposed that two variables are co-related, i.e. they go together in the sense that either:


a) as one variable increases (or decreases) so does the other = positive                 OR
b) as one variable decreases the other increases = negative

The strength of a relationship between two variables is the degree to which one variable does tend to be high if the other is high (or low, for negative correlation). The strength is expressed on a scale from + 1 (perfect positive correlation) through 0 (no relationship) to -1 (perfect negative).

The figure arrived to express this relationship is the correlation coefficient and this can be calculated for the relationship between any two variables.

Problems with correlation!

It is a common mistake to automatically assume that one variable causes the other to vary.
In fact in correlations a CAUSAL RELATIONSHIP is impossible to determine and there are 3 possible reasons for why 2 variables might be correlated:

1. A causal relationship
2. Both variables are affected by an unknown third variable
3. The correlation occurs by chance

For example: There is a positive correlation between bio-yogurt eating and the birth of 2 headed mutant babies. (sorry for the horrible example!)

There is a positive correlation between bio-yogurt eating and the birth of 2 headed mutant babies, (2)eating bio-yogurt can cause the birth of 2 headed mutant babies, (3) living right next to a nuclear power station can lead to people eating bio-yogurt, which can lead to the birth of 2 headed mutant babies.

A piece of Correlational research
Fourty-four thieves
MDH- Maternal Deprivation Hypothesis