# Correlation In Psychology

Correlation method is defined as “A research method used to examine relationships between variables, which are expressed in the form of a statistical measure called a correlation coefficients” (Nevid,201,p24). Unlike an experiment where one variable is dependent and the other is independent, both variables in a correlation remain constant. For each correlation, there are two or more variables. These variables can have a positive, negative

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Scatterplots are graphs with a horizontal and vertical axis used in mathematics to plot variables on. Scatterplots display positive, negative and zero correlations. When a graph is increasing upwards, the correlation is positive, and when it trends downwards the correlation is negative. If data points are scrambled all over the scatterplot, the correlation is nonexistent. There are many benefits to correlating. If a perfect negative or positive correlation is present, researches are enabled to predict events that could occur in the future. Furthermore, a well thought out hypothesis based on the relationship can produce new discoveries. For example, students with high attendance rates, receive higher grades. Researches can predict that students with multiple absences receive lower grades. Correlation also informs groups of people at high risk for physical or behavioral problems. For instance, humans overweight have a higher risk of heart attacks. Knowing this relationship, heavy weighted humans should take better care of their bodies and lose weight to reduce their risk of a heart attack. Lastly, the method of correlation increases our understanding of positive and negative events that are relatable. There are limitations of correlating set by causations. Correlations, including perfect ones, do not cause events to occur. For example, an increase in salary correlates with a higher position. A salary increase does not dictate a higher position at work. These variables are related because typically higher position earns more money. Two or more variables, associated with each other, examined carefully enable anybody looking at the data on a scatterplot to make bold predictions on the events