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 children’s 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. For example, consider a reported correlation that the number of books in a person’s home (predictor variable) is related to their college GPA (outcome). An extraneous variable could be, for example, a person’s IQ (intelligence quotient) score. The higher IQ might be related to higher college GPA but not necessarily related to the number of books found in a person’s home. There are additional examples of spurious relations and extraneous variables on pages 174–176 of your course text.

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.

**To prepare:**

- Review popular online newspapers and/or online magazines to look for articles on research studies. Look for examples of statements and claims that might reflect a spurious correlation or an extraneous variable.
**Note:**This is not a library assignment, nor should you look for articles that already have reported a spurious relation or extraneous variable. You need to make this connection yourself. For instance, you might see a headline in a news magazine that states something like “Fast-Paced Children’s Television Programming Linked to ADHD.” Look for examples like this. - Identify
**one**popular media example of a correlation that could be argued to be a spurious correlation**or**that illustrates a correlation that may have an extraneous variable.

**With these thoughts in mind:**

**Post** by **Day 3:**

- Briefly explain the example and the claim that has been made.
- Identify the predictor variable and the outcome variable.
- Identify the correlation. Is it a positive or negative correlation? How did you determine this to be the case?
- Identify your proposed spurious (third) variable
**or**extraneous variable. - Explain the connection you made among the spurious/extraneous variable and the outcome and predictor variables.
- Post the URLs for the media example at the end of your posting.

**Note:** Be sure to support the responses within your Discussion post, and in your colleague reply, with evidence from the assigned Learning Resources.