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What is meant by a spurious relationship between two variables?
A spurious relationship between two variables occurs when there appears to be a statistically significant association between them, but in reality, the association is not causal.
This happens when there is a third variable, known as a confounding variable, that affects both of the original variables. This third variable creates the appearance of a relationship between the original two variables, even though they are not directly related to each other.
EXAMPLE:
For example, a study might find a positive correlation between ice cream sales and crime rates. However, this does not mean that ice cream consumption causes crime or vice versa. In this case, the confounding variable is likely to be temperature, as both ice cream sales and crime rates are likely to increase when it’s hotter outside.
To determine whether a relationship between two variables is spurious or not, researchers need to carefully consider potential confounding variables and control for them in their analyses.
