Lectures for chemists on statistics II. The normal distribution: a briefer on the univariate case

Motivated by the introduction of a supplement to the GUM suggesting Monte Carlo simulation as a method for establishing a complete measurement uncertainty budget, some properties of the normal distribution are reviewed. The normal distribution is the central distribution of parametric statistics and sampling from normal distributions is a regularly occurring activity in statistical simulation by Monte Carlo methods. Algorithms for computer generation of normal deviates, areas under the normal curve, and the error function are given to encourage practical simulation. Some critical issues, e.g. coverage and influential observations, are presented. The discussion is restricted to the univariate situation. There is no intention to provide an exhaustive presentation. Statistics is a specialised field requiring sophisticated competences. The text may serve as a golden thread to acquire a quick survey on a subject of general interest.