To see if sample mean is an accurate estimate of Population mean, we use:
**Core Concept**
The concept being tested here is the principle of statistical sampling and its reliability in estimating population parameters. In statistics, the sample mean is used as an estimate of the population mean, but this estimate is only as good as the sample's representativeness of the population.
**Why the Correct Answer is Right**
The correct answer is the formula for calculating the standard error of the mean (SEM), which is a measure of the variability of the sample mean. The SEM is calculated as the standard deviation of the population divided by the square root of the sample size (n). This formula is used to determine the reliability of the sample mean as an estimate of the population mean. A smaller SEM indicates that the sample mean is a more accurate estimate of the population mean.
**Why Each Wrong Option is Incorrect**
**Option A:** This option is incorrect because it is not a formula, and it does not relate to the calculation of the standard error of the mean.
**Option B:** This option is incorrect because it is a formula for calculating the coefficient of variation, not the standard error of the mean.
**Option C:** This option is incorrect because it is a formula for calculating the standard deviation of a sample, not the standard error of the mean.
**Clinical Pearl / High-Yield Fact**
When interpreting sample means, it's essential to consider the standard error of the mean to evaluate the reliability of the estimate. A small SEM indicates that the sample mean is a more accurate estimate of the population mean.
**Correct Answer: C. σ / √n**