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There are differences between the concepts of correlations and causality. Correlation is a concept that can be used daily to symbolize some type of association (Hazra & Gogtay 2016). “The concept of correlation entails having a couple of observations (X and Y), that is to say, the value that Y acquires for a determined value of X; the correlation makes it possible to examine the trend of two variables to be grouped together” (Roy-García et al., 2019). The causality concept is often misunderstood. In statistics, one of the common errors with interpreting correlation is that there is a possibility of a third variable associated with the two variables being investigated, which is responsible for the correlation. It is critically important to make sure that the differences are understood between correlation and causality. It is wrong to assume that there is a cause-and-effect relationship between two variables that are correlated, even if the correlation is strong. “In other words, correlation does not imply causation” (Hazra & Gogtay 2016). Understanding the concepts of correlation and causality can produce positive outcomes in a clinical setting if used appropriately.

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Differences between the Concepts of Correlations and Causality
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1. According to the statement above what can you agree and or disagree?

The differences between the concepts of correlation and causality are important to understand when considering research studies and information. Causation is present in a research study when a factor directly causes an outcome. This is determined and confirmed when there is qualitative consideration and quantitative data that implies there is a relationship (Jacobsen, 2017, p.347). Correlation is a statistical measure that predicts change of one variable on another variable and is intended to determine if two or more group characteristics are associated (Jacobsen, 2017, p.348). Correlation can occur even though causation does not. Both of these concepts are imperative when reading and gathering information. It is important to decipher between causation and correlation as it allows for students or researchers to question information and decide what, if either, relationship occurs and how to interpret presented data. It is also critical to understand these concepts so that information can be transparent and scholars/students will be able to articulate this information regarding research results.

2. According to the statement above what can you agree and or disagree?

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