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Spurious Correlation
Spurious correlation is when two variables appear to be directly influencing each other when in reality they are not. Usually this misconception is caused by a confounding variable. DAGs (directed acyclic graphs) can help visualize which variables may influence each other and indicate if there is a possibility for a spurious correlation.
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Bayesian Statistics
Statistics
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KPU
Research Methods in Psychology - 4th American Edition @ KPU
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Directed Acyclic Graph (DAG)
Example of a Spurious Correlation: Chocolate and Nobel Prizes
What term describes a situation where two variables appear to be directly influencing each other, but in reality, their relationship is an illusion usually caused by a confounding variable?
A researcher discovers a strong positive correlation between the number of hours students spend on social media and their reported levels of anxiety. However, further analysis reveals that a third variable—academic workload—independently increases both social media use (as a coping mechanism) and anxiety levels. In this scenario, the original correlation between social media use and anxiety is best described as a spurious correlation.
A researcher discovers a strong positive correlation between a child's vocabulary size and their shoe size. However, further investigation reveals that this relationship exists because older children tend to have both larger vocabularies and larger feet. Match each component of this research scenario to the role it plays in illustrating a spurious correlation.
A researcher discovers a strong correlation between 'Time Spent Gardening' and 'Lower Stress Levels' but suspects the relationship is not causal. Arrange the logical steps of the analysis required to identify if this is a spurious correlation.
A researcher is critiquing a claim that 'Reading Fiction' directly causes 'Increased Empathy.' Upon evaluating the study's Directed Acyclic Graph (DAG), the researcher identifies that 'Openness to Experience' is a common cause for both reading habits and empathy levels. To accurately judge the validity of the original causal claim, the researcher must characterize the observed relationship as a(n) _____ correlation.
Match each term to its correct role in the context of identifying relationships between variables.
When two variables, and , have a spurious correlation caused by a confounding variable, , which of the following best describes the underlying relationship between these variables?