Sampling Bias
A bias in which a sample is collected in such a way that some members of the intended population are less likely to be included than others, which results in a biased sample (a non-random sample of a population (or non-human factors) in which all individuals, or instances, were not equally likely to have been selected).
Origin
The phenomenon was thrust into public consciousness by the catastrophic 1936 failure of The Literary Digest, whose poll of ten million people — drawn from telephone directories and automobile registrations — skewed toward the wealthy and wrongly predicted a Republican landslide. Two years earlier, Polish statistician Jerzy Neyman had presented his landmark paper on representative sampling to the Royal Statistical Society in 1934, laying the mathematical groundwork for understanding how biased selection frames distort results.