What are some real-world examples of sampling bias?

What are some real-world examples of sampling bias?

Sampling bias occurs when certain members of a population are systematically more likely to be selected for a study. One example is the 1936 U.S. presidential election poll, which only surveyed voters from landline telephones, missing a significant portion of the population.

Can you explain how that affected the election results?

Certainly! The poll predicted a landslide victory for Alf Landon over Franklin D. Roosevelt. However, the actual results showed Roosevelt winning by a large margin. The bias in sampling led to inaccurate predictions because it didn't represent the voting population accurately.

Are there other fields where sampling bias is a concern?

Yes, sampling bias is a concern in various fields, including healthcare, market research, and social sciences. For instance, in medical studies, if only healthy individuals are sampled, the results may not be applicable to the general population.

How can researchers avoid sampling bias?

Researchers can avoid sampling bias by using random sampling methods, ensuring diverse representation, and being transparent about their sampling techniques.