Correlational Research

Correlational research is used when a psychologist wants to know how two variables are related to each other, usually for the purpose of prediction, for example, whether the amount of time a student spends studying is related to their academic achievement. This differs fundamentally from the experimental method: in correlational research, the researcher does not manipulate one variable to observe its impact on another; they simply measure both variables as they naturally occur and determine whether, and how strongly, they are associated, or 'covary'. The strength and direction of this relationship is expressed as a single number called the correlation coefficient, which can range from +1.0 through 0.0 to -1.0. A positive correlation means that as one variable (X) increases, the other variable (Y) also tends to increase, and as X decreases, Y tends to decrease as well; more study time going with higher achievement scores would be an example, and the closer the coefficient is to +1.0, the stronger this positive association. A negative correlation means the two variables move in opposite directions, as X increases, Y tends to decrease, such as more time spent studying being associated with less time spent on other activities, with the coefficient here ranging between 0 and -1.0. A zero correlation means the two variables are essentially unrelated; true zero correlation (a coefficient of exactly 0.00) is uncommon in practice, so in real data a coefficient very close to zero (such as -.0 …