Final answer:
The standard set at a level that could be achieved if everything ran perfectly is known as the 'ideal standard.' It is distinct from practical or expected standards and aims for the highest precision, akin to measurements based on fundamental physical constants like those in timekeeping. The mean and standard deviation are statistical measures that help estimate the expected value and its variability.
Step-by-step explanation:
The standard described as one that could be achieved if everything ran perfectly is known as the ideal standard. Ideal standards represent a set of conditions that are, in essence, perfect and are often used as a goal for which an organization should aim, even though they are recognized as being not commonly attainable in normal operations. These standards differ from practical or expected standards, which are based on what you would expect to occur under typical conditions, taking into account some degree of variability and uncertainty.
As an example in the context of measurements and quality assurance, the quest for microscopic standards for basic units aims for the highest accuracy and precision, much like ideal standards. By basing measurements on consistent and fundamental physical phenomena, like the oscillations of a cesium atom for time measurement, we attempt to achieve a level of perfection in the standards.
In statistical terms, the mean and standard deviation are used to describe expectations about a dataset. The mean signifies the central value you would expect, while the standard deviation estimates the degree of variability or uncertainty around that mean. For example, if the mean time until a defective computer component is found is 50 units, the standard deviation informs us about the typical variation from that mean, which might also be 50 units in this scenario.