Final answer:
The formula µ = ± a sampling error represents the uncertainty or variation in a sample mean compared to the true population mean.
Step-by-step explanation:
The formula µ = ± a sampling error represents the uncertainty or variation in a sample mean compared to the true population mean in statistics and data analysis. The symbol µ represents the population mean, and the formula µ = ± a represents the range of values within which the true population mean is likely to fall.
For example, if the sampling error is ±0.2 units, it means that we can be 95% confident that the true population mean is within 0.2 units of the sample mean.
This formula helps us understand the level of uncertainty in estimating the population mean based on a sample, allowing us to make more reliable inferences about the population.