The purpose of psychological assessments is to accurately measure the relationship between two variables

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Correlation versus Causation 

The purpose of psychological assessments is to accurately measure the relationship between two variables. This can be done in various locations where test users order a test and interpret the data discovered. This can be performed through various locations including using computers online, in class, hospital or rehabilitation center. First, it is important to define correlation and causation and how they are connected.  

         The authors define correlation as an “expression of the degree and direction between two things” (Cohen et al., 2022). In addition, the coefficient of correlation is a representation of the degree of this connection between two variables. The coefficient of correlation is given a value sign of + or – to indicate positive or negative relationship. If the sign of the coefficient of correlation is positive with a + sign, the relationship is moving together either increasing or decreasing together. When the direction is not moving together, it is a negative correlation. In addition, when the correlation is zero, there is no relationship between the two variables. To measure the correlation, the Pearson r can be a useful measurement to the connection between two variables. The Pearson r is used to “convert raw scores to find the mean” (Cohen et al., 2022). There are also other forms of measuring the index of correlation including a rank-order correlation coefficient, rank-difference correlation coefficient, and the Spearman’s rho. The Spearman’s rho is used when “the sample size is small, and the variables are ordinal or ranked” (Cohen et al., 2022). When providing a graphic representation of correlation, researchers use a bi variate distribution, scatter gram, or scatter plot. A scatter plot provides a graphical representation of the correlation, with a positive or negative direction of degree. A scatter plot will provide visual spotting of outliers in the research. When points are scattered around the scatter plot, there is no correlation, however when the plot displays points that form a line, this shows a positive correlation with either a positive or negative strength of relationship. A perfect relationship will be a +1 or -1.  

          Correlation between two variables does not reflect causation but can provide the framework for prediction. Correlation does not mean that something is going to happen but can predict the possibility of something happening in the future. In a study of New York, there was a correlation between the increase in ice cream sales and homicides. Even though the findings showed that when ice cream sales went up the homicide numbers also went up, eating ice cream does not cause homicide (YouTube, 2019). However, there is a correlation between the two variables, however no cause and effect. The YouTube video summarizes that ice cream sales are higher when the weather is good, as well as homicides are more active when people are outside more often, with an increase in opportunity to interact. These two variables are correlated; however, one does not cause the other.  

References 

 Cohen, R., Scheider, J., Tobin, R. (2022). Psychological testing and assessment: An introduction to tests and measurement (10th ed.). McGraw Hill.  

 YouTube. (2019). Correlation Does Not Imply Causation: A one minute perspective on correlation vs. causation. YouTube. Retrieved November 2, 2022, from Correlation Does Not Imply Causation: A One Minute Perspective on Correlation vs. Causation 

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