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The London School of Economics have, since 1959, studied the jobs of supervisors in a number of plants to demonstrate their range and variety and the relation of supervisory systems to technology. A previous article (see below) on the first part of the research argued that there was no straightforward relationship between the two, but that organizational and human factors could also greatly determine supervisory jobs. This paper describes the last part of the research which was devoted to a far deeper and more detailed analysis of supervisory jobs in one large firm in an attempt to find more concrete evidence of different influences on supervisory jobs. The results show that the nature of the product, the technical situation, the factory organization, the supervisory training programme and the supervisor's personality all affected both his behaviour and the demands made on him. A supervisor was seen to be reacting to a continuous succession of pressures, some of which ran counter to others. The relative weighting of these against each other, as well as the supervisor's personality, affected the way in which he behaved as well as the subsequent demands made on his job. [ABSTRACT FROM AUTHOR]

Several approximations to the binomial distribution were compared in 1956 by Raft [9], including the normal, arcsine, normal Gram-Charlier, Camp-Paulson, Poisson, and Poisson Gram-Charlier approximations. The closeness of these approximations is judged by the maximal error which can arise in evaluating any sum of consecutive binomial terms. Borges [3] investigated a general class of approximations (which includes some of the above) and showed that a certain beta-transformation of a binomially distributed variable is the unique member of this class which is approximately normal with error 0(l/n). In 1963, Bol'shev [2] gave two new Poisson-type approximations. In this paper, some of Raft's tables are extended and tables for the error of these newer approximations are added. As a consequence of the numerical results obtained, the Poisson Gram-Charlier approximation is recommended for small values of p while the Camp-Paulson and Borges' approximations should generally be preferred for large p. [ABSTRACT FROM AUTHOR]

Data editing by a computer program can be regarded as a form of statistical quality control. In that perspective, costs and benefits of alternative programs can be compared to one another and, of course, to no control plan at all. This paper outlines one approach to cost-benefit comparison and utilizes a realistic example to suggest that computerized data editing is generally superior to clerical editing. It also warns against edit programs which provide for record rejections and off-line review. Most importantly, it urges that a systematic comparison of costs can assist significantly in edit planning. [ABSTRACT FROM AUTHOR]