How to Tell if a Data Sample is Good or Bad | Math and Science Review

Hi, and welcome this video lesson on data sampling. In math and science, we often see problems that involve data interpretation, where we interpret information like polling data or national birth rates, but how we gather that information matters just as much as how we interpret it.

When we take samples from a Petri dish, or a crowd, or anywhere else for that matter, we can either get a representative data sample or a skewed data sample. A sampling method that produced skewed data would be collected from a sample that wasn’t randomly selected, or that poorly represented the larger population.

For example, if a clothing store with a target population of 15 to 35-year-olds surveyed only customers that were between the ages of 15 and 16, the results of the survey would not be representative of the target population, 15 to 35-year-olds. Survey results would only reflect the opinions of a small portion of the target population.

A sampling method that produces data representative of a population is randomly selected and represents the whole population. For example, if a town wanted to gather opinions from its residents, the town could survey a random group of residents from each street in the town.

The survey participants would be both randomly selected, and residents of different regions in the town would be represented in the results. I hope that helps. Thanks for watching this video lesson, and until next time, happy studying!