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Many adults owe money from their college loans for years into their professional careers. a newspaper would like to estimate the proportion of all adults in the city who have debts from college loans. to collect data, a random sample of 300 young adults between the ages of 25 and 35 is asked, "do you have more than $5,000 in current college debts?" 68% of those sampled reported that they do have more than $5,000 in college-related debts. how might this sample be biased in obtaining an estimate of all adults in the city who have college debts?

Sagot :

Because only young adults were sampled, undercoverage bias may cause the newspaper to overestimate the proportion of all adults who have college debts.

What is bias in sampling?

When a sample is chosen in statistics, sampling bias is a bias that causes some individuals of the target population to have a lower or greater sampling probability than others. As a result, not every person or event was equally likely to have been chosen, resulting in a biased sample of a population (or non-human variables).

If this is not taken into consideration, results may be incorrectly attributed to the sampling procedure rather than the phenomenon being studied. Although some people identify sampling bias as a distinct sort of prejudice, sampling bias is typically categorized as a subtype of selection bias, sometimes referred to as sample selection bias.

Learn more about sampling bias with the help of the given link:

brainly.com/question/11094051

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