The goal of correlation research strategy is to show that two or more variables are related, like good grades and hours of sleep, for example. However, correlational research cannot be used to demonstrate a cause and effect relationship between variables. This kind of strategy It is useful for preliminary research and verifies if those two variables are effectively related before starting deeply investigations in controlled experiments.
The data collected of a correlational study is expressed by scores for each participant and are correlated in a graph called scatter plot to posterior analysis and evaluation of each pair of scores. Three important aspects are considered to measure the relationship between the variables: the direction, form, and consistency of the relationship.
The direction of a relationship differs in two ways. It can be positive, as the number on the X-axis increases, so does the number on the Y-axis, and also can be negative, when the line slopes down, this means that as the score on the X-axis gets higher the number on the Y-axis gets lower. It can be said that cancer and smoke have a positive correlation while age and collagen production has a negative correlation, for example.
The form of the relationship depends on the form of the scatter plot. The relationship can be linear when the scatterplot looks like a straight line. Variables can also have a nonlinear or monotonic relationship. In a monotonic relationship, the variables tend to move in the same relative direction, but not necessarily at a constant rate like in a linear relationship, which variables move in the same direction at a constant rate. If there is no relationship between the variables the scatter plot looks like a big mess of dots, impossible to make a reasonable connection between variables.
A positive linear relationship:
A monotonic relationship :
The strength and direction of a monotonic relationship between two variables can be measured by the Spearman Correlation. If the variables are linear, a more appropriate test might be Pearson’s Correlation. Overall, the strength/consistency of the correlation refers to how close the value of the correlation coefficient is to 1 ( strong correlation) or -1. A correlation of zero or near zero indicates no relationship at all.
Correlational Studies have several applications in real life. They are critical to show that one variable is useful for predicting another, assess the reliability and validity of measurements procedure and therefore, evaluate theories. For example, if a researcher wants to evaluate a theory that junk food is linked to colon cancer, he might correlate the amount of this kind of food that is consumed by the individuals to with the incidence of colon cancer. The correlational strategy is essential to promote early investigations and collect basic knowledge for further studies to establish cause and effect.
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