Polls based on samples of populations are subject to sampling error which reflects the effects of chance and uncertainty in the sampling process. Sampling polls rely on the law of large numbers to measure the opinions of the whole population based only on a subset, and for this purpose the absolute size of the sample is important, but the percentage of the whole population is not important (unless it happens to be close to the sample size). The possible difference between the sample and whole population is often expressed as a margin of error - usually defined as the radius of a 95% confidence interval for a particular statistic. One example is the percent of people who prefer product A versus product B. When a single, global margin of error is reported for a survey, it refers to the maximum margin of error for all reported percentages using the full sample from the survey. If the statistic is a percentage, this maximum margin of error can be calculated as the radius of the confidence interval for a reported percentage of 50%. Others suggest that a poll with a random sample of 1,000 people has margin of sampling error of ±3% for the estimated percentage of the whole population.