ABSTRACT
The concept of standard error is one that many students of statistics find confusing when they first encounter it. In all honesty, there are many students, and many researchers, who never fully grasp the concept. I am convinced that many people have problems with understanding standard errors because they require a bit of a leap into the abstract and because, with the advent of computer programs, it is possible to lead a long and productive research life without having to think about or analyze a standard error for years at a time. Therefore, many researchers choose to gloss over this abstract concept. This is a mistake. I hold this opinion because, as a teacher of statistics, I have learned that when one is able to truly understand the concept of standard error, many of our most beloved inferential statistics (t tests, ANOVA, regression coefficients, correlations) become easy to understand. So let me offer this piece of advice: Keep trying to understand the contents of this chapter, and other information you get about standard errors, even if you find it confusing the first or second time you read it. With a little effort and patience, you can understand standard errors and many of the statistics that rely on them.
