Correlation - Sample Paper
Updated: Jun 9, 2022
There are a number of statistical techniques that can be used to show relationship between variables in sets of data as covered in the course materials. One such statistical technique is the use of correlation. Correlation is indeed an important statistical test that shows how pairs of variables relate to each other. In fact, the main purpose of correlation is to show how strongly these pairs of variables relate. Therefore this paper will explore how correlation has been used to show the relationship between students’ SAT test scores and their family income.
From the correlation given, it is evident that it is a positive correlation. Basically, this means that both variables move in Tandem. In other words, if one variable decreases, then the other also decreases and vice versa. So in the case of the correlation between SAT scores and family income, the correlation tells us that high income correlates with high SAT scores and vice versa (Coolican, 2014).
Unfortunately we cannot conclude that having high family income causes one to have high SAT scores or high SAT scores causes one to have high income. This is because one of the disadvantages of correlation is that it does not measure cause and effect. In fact, the statement can go either way and no one really knows if family income causes one to have high SAT scores or it is high SAT scores that cause high income. Therefore, all that correlation shows us is the relationship between the two variables (Coolican, 2014).
Generally, correlation alone is not sufficient to demonstrate cause and therefore, if one needs to measure cause and effect, then choosing another statistical testing technique may be a good idea. For instance, one can choose t tests to measure cause and effect and then go ahead and use correlation to show the relationship between the two variables.
Coolican, H. (2014). Research Methods and Statistics in Psychology. Psychology Press.
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