For which of the following $\mathrm{population}\mathrm{parameters}$ is $\mathrm{sampling}$ not necessary?

• A. When the $\mathrm{population}$ is too large to access
• B. When only an estimate of the $\mathrm{parameter}$ is needed
• C. When the entire $\mathrm{population}$ can be measured directly
• D. When the $\mathrm{population}\mathrm{parameter}$ is unknown

Answer: (C)

Verified step by step guidance

1. Understand the concept of a population parameter: it is a value that describes a characteristic of an entire population, such as the mean or proportion.
2. Recognize that sampling is used when it is impractical or impossible to measure the entire population, often due to size or accessibility.
3. Identify the condition where sampling is not necessary: this occurs when the entire population can be measured directly, meaning you have complete data for every member.
4. Compare the given options and note that if the population is too large or the parameter is unknown, sampling is typically required to estimate the parameter.
5. Conclude that sampling is unnecessary only when the entire population can be measured directly, as this allows for exact calculation of the population parameter without estimation.