Standard Error of Estimate (SEE)
Standard Error Estimate is use to find the accuracy of prediction of any event. Its abbreviation is SEE. Standard Error Estimate (SEE) is also called the Sum of Sqaures Error. SEE is the square root of average squared deviation.
Standard Error of Estimate(SEE) formula is discussed below,
SEE = √[Σ(xi – μ)/(n – 2)]
where,
- xi is values of Data
- μ is Mean Value of Data
- n is Sample Size
Standard Error
Standard Error is the measure of the variability of a sample statistic used to estimate the variability of a population. Standard Error is important in dealing with sample statistics, such as sample mean, sample proportion, etc. Sample Error Formula is used to determine the accuracy of a sample that reflects a population. The standard error formula is the discrepancy between the sample mean and the population mean.
In this article, we will learn about, Standard Error, Standard Error Formula, Standard Error of Mean, Standard Error of Estimate, related Examples, and Error in detail.