Answer:
Down below
Explanation:
Biased sampling can affect the statistical study of a population by not having a variety of samples and there would either be all evidence supporting one side, but not talking about the other. Example: Someone is put on jury duty and knows the person being accused. That would be an example of biased because whether you know the person in a good or bad way, you decesion on if they are guilty or not guilty would naturally be on how you feel about them. Although this example doesn't pertain to the question given, the biased sampling would be innaccurate. A better example would be if a scientist wanted to know if all people with the flu were depressed. Let's say that scientist only asked depressed people with the flu if they were depressed, that would be innaccurate and the conclusion might be that all people with the flu are depressed.
Sorry if my explanation confused you.
