Final answer:
Sampling variability is the term used to describe how much a parameter estimate deviates from the true value in repeated sampling and it is measured by the standard error.
Step-by-step explanation:
The statistical term that describes the degree to which a parameter estimate consistently deviates from the true value in repeated sampling is known as the sampling variability of a statistic. We measure this variability by the standard error, which is the standard deviation of the sampling distribution, indicating the average standard deviation that results from repeated sampling.
This concept is critical in inferential statistics, where we use sample data to make generalizations about an unknown population. A low standard error indicates that the parameter estimate is relatively precise and consistently close to the true population parameter across different samples.