PYSC 3003 Methods In Psychological Inquiry

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PYSC 3003 Methods In Psychological Inquiry

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PYSC 3003 Methods In Psychological Inquiry

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Course Code: PYSC3003
University: Walden University

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Country: United States

Question:

Discussion: Spurious Correlations and Extraneous Variables
Correlational research describes relations among variables but cannot indicate that one variable causes something to occur to another variable. Rather, a statistically significant correlation coefficient simply indicates there is a relation among a predictor variable and an outcome variable.
In correlational research, if there is a statistically significant correlation coefficient between two variables, you want to know that the relation truly exists. This goal is challenging to achieve because other variables that you are not studying may complicate the study and the interpretation of the results.
You may find a spurious relation in which one common causal variable, sometimes referred to as a third variable, is responsible for the observed relation between the predictor variable and the outcome variable. Imagine seeing a news story reporting the findings of a study claiming that children under the age of 17 who viewed R-rated movies showed a greater likelihood of developing a smoking habit. A third variable that could explain both the predictor and outcome variables is permissive parenting. Permissive parents may allow children to view R-rated movies when they are under the age of 17. In addition, permissive parents may not attend to their children’s whereabouts enough to be aware of their smoking habit, or they may not discipline the children for smoking. Therefore, in effect, you cannot conclude that the movie viewing caused the smoking habit. The permissive parenting may have led to the childrenss movie viewing habit and their smoking habit.
You may also identify extraneous variables that might influence the outcome variable but, unlike the spurious correlation described above, these variables do not relate to or influence the predictor variable.In this Discussion, you focus primarily on spurious relations and extraneous variables. After reviewing examples in the course text, you will find your own examples in the media and explain how they might affect the relations between the variables under consideration.

Answer:

Spurious correlation is the relationship between two variables which does not result from any relationship between the two variables however from its relation to additional variables. On the other hand, extraneous variables are variables that affect the outcome of an experiment other than the independent and dependent variable(Nugent, 2017). Extraneous variables are considered to bring about an error in the experiment(T Wilson & Shuttleworth, 2017).
Example
One student had gone out partying the weekend before, and while sitting in the bar watching his friends during the evening, he noticed that people who had the most fun dancing were also those who were most likely to throw up by the end of the evening(“Spurious Correlation Explained With Examples”, 2017).
In this example, there are the independent variable, dependent variable, extraneous variable and spurious correlation. In this case being sick is not out of dancing neither does being sick made the students have fun. Instead, there is an extraneous variable of consumption of alcohol. Alcohol consumptions lead to dancing and throwing up. If having fun dancing made the students sick, there must be a positive correlation between having fun dancing and being sick. This is to mean that it cannot be expected that every time having fun dancing at a party(independent variable), being sick will also occur(dependent variable) or be sick will only happen after student having fun dancing at a party.
The temporal relation is another factor that could allow inference to be drawn from the associated variable relationship (stangor, 2015). Suppose having fun occurs before being sick, then a conclusion could e brought that being sick is caused by having fun. However, if being sick only happens before having fun dancing at a party, then having fun could not be creating being sick of the student. Then being sick cannot be a casual variable if it only happens after dancing at the party.
The predictable variable is a variable that is often manipulated to test the outcome of the dependent variable. On the other hand, the dependent variable is variable that is put under test for experimental purposes. As the researcher changes the predictor variable, the influence is observed on the outcome variable and recorded down. In the above example, the experimenter wants to see attending a party and having student’s dance has any effect on the student being sick. The researcher observes those students who had most fun dancing. This would be the predictor variable. How the students felt after that is the outcome variable.
The relationship between the predictor variable and the outcome variable has some extraneous variables.it is not logic to conclude that every time the student attends a party, have most fun dancing will end up being sick. There is an extraneous variable that causes the outcome of being sick. Some of extraneous variable include: first, suppose students attend the party and expose themselves to cold all night, this could cause sickness such as flue. Secondly, assume the student has health issues before attending the party. Thirdly, suppose the researcher only selected student with health conditions to participate in the party to manipulate the result. Lastly, assume the student consumed a lot of alcohol while at the party that brought about the feeling of the hangover the following day.
Connection made among spurious variable, outcome variable and predictor variable is as follow: First, considering the student attended the party, consumed no alcohol, but had fun dancing all night, this could cause a different outcome. Secondly, if the students participated in the party, consumed alcohol of varying variety, without even dancing, could cause a student to be sick the following day. Thirdly, if the student had health conditions, such as ulcer before attending the party, consumed alcohol that contained methanol, the student is likely to fall sick without even dancing at the party. Lastly, the student who attended the party might have fallen sick due to consuming a lot of alcohol and abusing other drugs and dancing at the party causing fatigue.
References
URL:https://psychologenie.com/spurious-correlation-explained-with-examples
Nugent, P. (2017). What is EXTRANEOUS VARIABLE? definition of EXTRANEOUS VARIABLE (Psychology Dictionary).PsychologyDictionary.Retrieved6November2017,from https://psychologydictionary.org/extraneous-variable/ 
Spurious Correlation Explained With Examples. (2017). PsycholoGenie. Retrieved 6 November 2017, from https://psychologenie.com/spurious-correlation-explained-with-examples.
T Wilson, L., & Shuttleworth, M. (2017). Confounding Variable / Third Variable.. retrieved Nov 01, 2017 from Explorable.com:. Retrieved 6 November 2017, from https://explorable.com/confounding-variablesstangor, c. (2015). Research methods for the behavioral sciences (5th ed.). Stamford,CT: Cengage Learning.

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