Industrial applications of some techniques in statistical modelling

A wide variety of techniques in statistical modelling can be applied to industrial problems. Procedures based on the generalised linear model may be applied to problems in which ordinary least squares is appropriate, due to nonnormality in the error structure. In this paper, a brief description will be given of the application of log-linear models to problems posed in industry in fields as diverse as pharmacology and software reliability. In industrial quality control, the serial correlation in successively sampled data: a's often mistakenly ignored. The second part of the paper focuses on the use of ARIMA models for describing industrial processes in which autocorrelation is present. The variogram is used to identify processes which may be described via the random coefficient model, with applications to stock market prices.