Response to First Discussion. Psychology Coursework (Coursework Sample)
Please respond to the following two discussions please refer to order #00078999. Agreements/Disagreements, Add-on, etc.
First Discussion to Respond to:
First of all, lets define what correlations are to get a better understanding of the overall question. Correlations are two or more variables that are related or have an association. In psychology we conduct correlational studies to understand how the variables relate. "There are three possible results of a correlational study: a positive correlation, a negative correlation, and no correlation. A positive correlation is a relationship between two variables in which both variables either increase or decrease at the same time" (Saul McCleod, 2018). For example, the longer your hair grows, the more shampoo you will need.
There is phrase we often hear, "correlation does not imply causation". Why is this? You need an independent and dependent variable for these to coexist with each other. It's more difficult to establish cause and effect than it is to establish correlations. For example, does us owning pets allow us to live longer and more healthy lives? How do we establish causation? "The use of a controlled study is the most effective way of establishing causality between variables. In a controlled study, the sample or population is split in two, with both groups being comparable in almost every way. The two groups then receive different treatments, and the outcomes of each group are assessed" (Abs.gov, 2013). Another example, one group receives the placebo and the other receives the medication. The groups will have a noticeable outcome because of the different control groups. To establish correlation and causation, you need to observe these groups to see what changes occur over time.
There have been so many correlational studies to establish causation. In correlation, events or things predicts another. There have been many studies linking guns to homicides in the United States. However, one does not cause another. In fact, areas with higher percentage of gun ownership has seen an increase in homicides, this is a correlation not causation. I only bring this study up because it has been a hot button issue for quite some time. There is a higher amount of suicides with guns than homicides.
Australian Bureau of Statistics. (2013, July 3). Retrieved January 24, 2019, from http://www(dot)abs(dot)gov(dot)au/websitedbs/a3121120.nsf/home/statistical language - correlation and causation
McLeod, S. (2018, January 01). Correlation. Retrieved January 24, 2019, from https://www(dot)simplypsychology(dot)org/correlation.html
Correlation can be defined as a statistical measure which indicates the extent in which two or more variables mutually fluctuate. Furthermore, a positive correlation indicates the extent to which fluctuating variables increase or decrease in a result of one another. A negative correlation indicates the extent to which one variable tends to increase as the other decreases. However, when discussing a correlation coefficient, it is important to note that the measure of degree that differs in value of one variable can predict change to the other variable. Although, there is a misconception that the fluctuation of one variable accurately predicts the outcome of the other variable. In layman’s terms, a plethora of people assume that the change in one variable will cause the other variable to change as well. Yet, correlation cannot be inferred through causation. Hence, there could be some undisclosed information or factors holding authority on the variables.
That being so, correlation is not causation, nor does it mirror the definition. Just because two variables are correlated to one another does not necessarily lend fact to one causing the other. Correlation and causation are often used interchangeably. However, building a firm understanding that correlation is something people tend to think when other information is not visible, and causation is the cause and effect in a relationship, can help people comprehend the differing characteristics between the two. To illustrate, the less information we have the more we are forced to observe specific correlations. Hence, the more information in our possession the more transparent events will become and the easier we will be able to make accurate conclusions on relationships.
In researching this topic, I stumbled on a fascinating journal article which stated that the correlation between grades of instruction and student satisfaction has been interpreted as providing insight to the relationship between the grades students expected to receive and their evaluations of the instructor. Meaning that the easy graders receive better course evaluations than the harder graders because they are easy graders, simple as that. However, the journal states that there are several models that explain the correlation of grades with satisfaction are delineated. (Howard & Maxwell, 1980) Hence, it is easy to get caught up in the causation misconception in this scenario. In conclusion, correlation is not causation. Correlations between two factors can be caused by a third factor that can have the ability to affect both factors at hand.
Howard, G. S., & Maxwell, S. E. (1980). Correlation between student satisfaction and grades: A case of mistaken causation? Journal of Educational Psychology, 72(6), 810-820. doi:http://dx(dot)doi(dot)org(dot)ezproxylocal(dot)library(dot)nova(dot)edu/10.1037/0022-0622.214.171.1240
Response to First Discussion
Correlations can be in the same direction or opposite correlations where the strength of such correlations is reflected in the relationships like Spearman Rank and Pearson correlation coefficients, but not the strength of the possible context. The identified correlations ought to be examined more closely, and even when there is a logical connection between the variables, this does not mean a cause-effect relationship exists. Causality is the principle of cause and effect which indicates there is a direction individually. This implies that two variables such as x and y should be considered simultaneously to determine whether there is a relationship between them. In this case, such a relationship can be assumed but does not have to exist, if the variables correlate with one another. In most cases when there is causality, there is a correlation.
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