Standard error is the standard deviation of what distribution?

Standard error is the standard deviation of what distribution?

• A. How spread out the population values are.
• B. How much variability there is in the statistic across samples.
• C. The spread of individual scores.
• D. The dispersion of residuals in a regression.

Answer: (B)

The standard error measures how precise a statistic is by looking at how much that statistic would vary if you repeated the study many times with different samples from the same population. It is the standard deviation of the sampling distribution of the statistic—that is, the distribution of the statistic across samples. This tells you how much your estimate (for example, a sample mean) would vary from one random sample to another due to sampling error. It does not describe the spread of individual scores in the population or in a single sample (that would be the data’s standard deviation), nor the dispersion of residuals in a regression (a related but separate concept). So the standard error is best described as the standard deviation of the statistic across samples.

The standard error measures how precise a statistic is by looking at how much that statistic would vary if you repeated the study many times with different samples from the same population. It is the standard deviation of the sampling distribution of the statistic—that is, the distribution of the statistic across samples. This tells you how much your estimate (for example, a sample mean) would vary from one random sample to another due to sampling error. It does not describe the spread of individual scores in the population or in a single sample (that would be the data’s standard deviation), nor the dispersion of residuals in a regression (a related but separate concept). So the standard error is best described as the standard deviation of the statistic across samples.