Do you agree or disagree with the following? Is there anything you would add?

The difference between a sample and a population is that a sample is a subset group within a population and a population is an entire group that can include subsets. The population is general data, while the sample is specific to a subset within the population. Samples are done by collecting observations from the population. Since the sample is derived from the population - the sample group is always smaller than the population and hence, offers more specific information. The sample is what is being measured.

If I were doing a study on prices of the most popular meals in fast-food restaurants (ex: #1 on the McDonald's menu is the Big Mac Meal and the #1 on the Burger King menu is the Whopper Meal) my population would be Fast Food Restaurants which would include McDonald's and Burger King and my sample would be the prices for the Big Mac Meal and the Whopper Meal.

A sampling error happens when the sample doesn't represent the population data or is biased. Sample errors can be decreased by increasing the sample size. Increasing the sample size will allow the sample to more adequately reflect the entire population which will reduce deviations.