An article headline claimed that "Drugs Cause Homelessness" due to a positive relationship found between homeless populations and drug use. Educated psychologists thought this might be flawed, because they thought unemployment was influencing both drug use and homelessness. The impact of unemployment on both is an example of:

a confounding variable

an illusory correlation

a negative correlation

a reverse correlation

a confounding variable or third variable

Explanation:

Confounding variables are called the third variable or extra variable. These variables can ruin an experiment and its result. It shows a correlation between these variable but in actual, there was not found any variable correlation. These variables create biases in experiments. So this variable must omit from the experiment. It increases the variance in the experiment. Bias is an error in data collection or measurement. It can be omitted by random sampling.

For example, Unemployment could be a confounding variable in it.