Question

Which of the following describes an illusory-correlation bias?

1) When you correlate variables that do not exist in your data set.
2) When you incorrectly assume a correlation because there is an illusory confounding variable.
3) When you incorrectly assume a cause and effect relationship because two variables are correlated.
4) When you correlate a variable with a confounding variable.

Answer 1

An illusory-correlation bias is when people incorrectly assume a correlation between two variables that doesn't exist. It can be caused by confirmation bias, limited information, or the presence of confounding variables. A well-known example is the belief in a correlation between the moon's phases and human behavior.

Step-by-step explanation:

An illusory-correlation bias refers to the tendency to incorrectly assume a correlation between two variables when no such relationship exists.

One example of this bias is the belief that the moon's phases affect human behavior, despite no scientific evidence supporting this claim. Illusory correlations can arise from various factors, such as confirmation bias, limited information, or the presence of confounding variables.