Standard error (SE):
- The standard error is a measure of the precision or accuracy of a statistical estimate, typically expressed as a margin of error.
- It represents the standard deviation of the sampling distribution of a statistic, which is the distribution of all possible sample estimates that could be obtained from repeated sampling of the population.
- A smaller standard error indicates a more precise estimate, meaning that the sample statistic is less likely to deviate from the true population parameter.
- It provides a range within which the true parameter value is likely to fall with a specified level of confidence.
Nonstandard error (NSE):
- A nonstandard error is an estimate of the standard error that is calculated using a method that differs from the standard formula for standard error.
- Nonstandard errors are typically employed in situations where the standard error cannot be directly calculated due to the complexity or specific characteristics of the data or statistical model.
- In such cases, specialized methods or approximations are used to estimate the standard error, taking into account the particular features of the data or model.
- Nonstandard errors can provide valuable information about the uncertainty of estimates in non-standard situations.