This paper presents the Agresti & Coull "Adjusted Wald" method for computing confidence intervals and margins of error for common proportion estimates. The presented method is easily implementable by business students and practitioners and provides more accurate estimates of proportions particularly in extreme samples and small…

Although the use of simulation to teach the sampling distribution of the mean is meant to provide students with sound conceptual understanding, it may lead them astray. We discuss a misunderstanding that can be introduced or reinforced when students who intuitively understand that "bigger samples are better" conduct a simulation to…

Every measurement in science, every experimental decision, result and information drawn from it has to cope with something that has long been named by the term "error". In fact, errors describe our limitations when it comes to experimental science and science looks back on a long tradition to cope with them. The widely known way to cope…

The subject of uncertainties (sometimes called errors) is traditionally taught (to first-year science undergraduates) towards the end of a course on statistics that defines probability as the limit of many trials, and discusses probability distribution functions and the Gaussian distribution. We show how to introduce students to the concepts of…

Investigates minimizing errors in computational methods commonly used in chemistry. Provides a series of examples illustrating the propagation of errors, finite difference methods, and nonlinear regression analysis. Includes illustrations to explain these concepts. (MVL)