Often, students or employees will be asked to draw a conclusion from a huge amount of data. That’s when a sample is introduced. When a sample is accurate, it can represent the whole group. But when it is wrong, sampling error would occur. In statistics, sampling error or estimation error is caused by observing a single sample instead of the whole population. Sampling error can be found by subtracting the value of a parameter from the value of a statistic. Generally, there are two methods of reducing sampling error: increasing the sample size, and ensuring that the sample can adequately represent the entire population. Question: The professor uses one experiment to illustrate the definition of "sampling error". Explain how this example is related to the reading passage.
