On this page, we mainly discuss definitions of error and other associated concepts. Namely, this page will help to clarify some potentially confusing terminology, before we encounter it later on.
Error
It is important to make the distinction between the terms error and residual. The term error is used fairly loosely in many cases, but formally it refers to the difference between a measureed value and the expected value, μ, so the error is (xi - μ).This value is not observable through experimentation, however, since μ is the population mean and cannot be determined by measurement. The error is generally used to compare an experimental result to an accepted or given true value, such as the published literature value, or a value quoted by a manufacturer.
Residual
*
The residual is the difference between a single observed value and the sample mean, 
and mathematically looks like 
. The residual is a comparison between each individual measurement
and the set of measurements. By the looking at the residuals, we can get an idea of the quality of our data set and measurement
technique. The residual was also used to calculate the variance and standard deviation on the
previous page.
That concludes this section on the basics of statistics in Analytical Chemistry. Continue to the next section for a discussion of linear regression and the construction and use of calibration curves.