Answer:
The difference between the sample statistic and population parameter is called sampling error.
Step-by-step explanation:
We are given the following in the question:
- A sample is a part of population, it is a subset of population.
- A sample statistic describes the sample. It is a characteristic of sample and different from the population.
- A parameter describes the population. It is characteristic of a population.
- A sample may not be able to represent the whole population and this may lead to error.
- Thus, sampling error is the difference between the sample statistic and population parameter.
- It arises when the sample is not able to describe the population.
The difference between the sample statistic and population parameter is called sampling error.
