Effective Statistical Training in the Work Place

Article

Mast, W. Gerald   (1988, ASQC)   IBM Corporation, Rochester, MN

Annual Quality Congress, Dallas TX    Vol. 42    No. 0
QICID: 3500    May 1988    pp. 680-683
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Article Abstract

Statistical training is often wasted effort in the work place, primarily due to lack of support from management and lack of interest on the part of the work force. Both of these causes are often rooted in a major misunderstanding as to how statistical methods can actually be applied to the job at hand. Traditional statistical classes are generally theoretical and heavily math oriented, and the techniques taught are neither directed toward practical applications, nor tied to job-related skills.

Statistical training must be presented in a simple, straightforward, nonthreatening manner, and must be demonstrated to be a practical and helpful tool in the work place if it is to be endorsed by management and accepted by the work force.

The author draws upon his experience as an in-put teacher of statistics to discuss the elements of statistical training that must be present to stimulate understanding and acceptance. General course structure and topical content are discussed, emphasizing the link between the classroom and actual application in the work place. Study materials, exercises, assignments, and demonstrations all need to reflect this link. The content of courses for hourly, supervisory, and management levels all need to provide a common base of understanding, while allowing for different levels of expertise.

The selection and responsibilities of the trainer are explored in detail, and the merits and deficiencies of in-house vs. Outside instructors are compared. The use of various self-study methods as a statistical training vehicle is discussed, and include programmed instruction, videotape courses, and computer-based training. The effectiveness of such programs is directly proportional to the motivation and diligence of the student, and various ways of creating and maintaining that motivation are considered.

Keywords

Statistics


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