Sampling error refers to the difference between the results obtained from a sample and the actual values in the entire population. This error occurs because a sample is only a subset of the population, and it may not perfectly represent the characteristics of that larger group. For example, if a survey is conducted using a small group of people, the findings may not accurately reflect the opinions of the entire population. The size of the sample and the method of selection can influence the degree of sampling error. A larger sample size generally reduces sampling error, as it is more likely to capture the diversity of the population. Additionally, using random sampling techniques can help ensure that every individual in the population has an equal chance of being included, further minimizing potential errors.