In sampling, which quantity is used to estimate a population parameter?

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Multiple Choice

In sampling, which quantity is used to estimate a population parameter?

Explanation:
A value computed from the sample data, known as a sample statistic, is used to estimate a population parameter. The population parameter is the true, fixed value describing the whole group, but it’s usually unknown. By taking a sample and calculating something like the sample mean or sample proportion, you get a point estimate for the corresponding population parameter. The idea is that this sample statistic serves as the best available guess for the parameter given the data you collected. The other terms describe different ideas: a population parameter is the quantity you’re trying to learn about the population; a sampling error is the difference between your estimate and the true parameter (the error inherent in using a sample); a confidence interval is a range around the sample statistic that is believed to contain the parameter with a certain level of confidence, reflecting the uncertainty of the estimate.

A value computed from the sample data, known as a sample statistic, is used to estimate a population parameter. The population parameter is the true, fixed value describing the whole group, but it’s usually unknown. By taking a sample and calculating something like the sample mean or sample proportion, you get a point estimate for the corresponding population parameter. The idea is that this sample statistic serves as the best available guess for the parameter given the data you collected.

The other terms describe different ideas: a population parameter is the quantity you’re trying to learn about the population; a sampling error is the difference between your estimate and the true parameter (the error inherent in using a sample); a confidence interval is a range around the sample statistic that is believed to contain the parameter with a certain level of confidence, reflecting the uncertainty of the estimate.

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