SYMPOSIUM ON STATISTICAL METHODS IN EXPERIMENTAL AND INDUSTRIAL CHEMISTRY Introductory Remarks B. L. CLARKE, Merck & Co., Znc., Rahzuay, N . J .
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K O convictions have crystallized in the minds of many of us during the last five years or so: (1) Statistical methods of dealing with data have been neglected by the chemist, compared to the manufacturing engineer and the biologist, for example ; and (2) modern statistical technique has a great deal to offer i n both experimental and applied chemistry. About the only place in the curriculum where the average chemistry student comes into contact with statistics is in quantitative analysis where the theory or error is considered. Some years ago a prominent statistician and I critically evamined a number of standard treatises on analysis with respect to their treatment of error theory. I was shocked to be told by my specialist colleague that none of the authors of these texts seemed aware that anything had happened in statistical theory since 1890! A very great deal has happened in statistics since that time. However, it is not indeed too great an exaggeration to compare most of our quantitative analysis texts with a treatise on the applications of statistical niethods in which the chemistry chapter took no cognizance of the discovery of radioactivity and its sequelae. In support of the contention that statistics has much to otfri
us, it can be said that the modern statistical nicthodologist claimr. to the experimental chemist, including the analytical chemist, that he can point out (1) how to design his experiments so as to obtain the most useful body of data; and (2) how to marshal and organize the data so obtained in order that they shall speak with all their potential eloquence. Also, the expert in control charts and rclated methods tells the manufacturer, the processor, and the packager of chemical products that he can detect the existence of trends that may result in substandard products. earlier than by any other means, so that their causes mav bv corrected brfore great harm is done. So with the conviction that chemistry, although it needed to use statistical methods, was in fact not doing so, Walter Shewhart of the Bell Telephone Laboratories, Grant Wernimont of Eastman Kodak, and I organized this symposium, a t the request of the officers of the Divisions of Analytical and U c r o Chemistrv and of Industrial and Engineering Chemistry. The general plan is based on two assumptions: that the average chemist in our audience knows very little about statistics: and that a “selling job” has generally got to be done to persuade the management of evpcrimcntal and production units to trv out these new ideas.
The Management Viewpoint GEORGE F. SMITH, Johnson & Johnson, !Yew Brunswick, S. J . Various general applications of statistical methods are discussed H ith particular reference to a number of problems of interest to industrial management. Adaptation of the methods of opinion research to problems in market research is explained. The use of statistics in modern methods of sales forecasting is outlined. Examples are given of the use of statistical methods as a tool in helping the modern business executive adopt a factual approach to problems of marketing, selling, and production planning.
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HE layman usually thinks of statistics as involving more or less abstract mathematical considerations. For example, we have heard how astronomers, by application of*the theory of error, arrive a t a final result of exceedingly small probable error by proper averaging of a very large number of observations, each of which is characterized by a large uncertainty. Or, one may bring to mind the masses of statistics from which some economists are so wont to draw the wrong conclusions. Or, one may recall a cardplayer’s estimate of the probability of his drawing a certain card, forgetting that the laws of probability apply accurately only to very large numbers of events. Statistical theory is, of course, very old; but, as with other very old principles, new applications are often only lately discovered. Even in science, many practical applications of statistical theory have only relatively recently been made. Many applications of statistical theory in industry have come even more recently. One of the early applications of statistical theory t o practical technical problems was in sampling heterogeneous ran‘ materials.
For example, a mathematician can calculate what kind of samplts of coal must be taken from a carload in order to achieve a given accuracy in analysis of it as representative of the whole carload. if he knows the maximum variation in composition and the distribution of size of the lumps; and in the application of medical science to the inheritance of blood types, statistical theory is used. Statistics were applied during the war in the so-called “Operations Research.” Statistical methods were used to predetermine the effectiveness of various methods of attack. The methods used in combating the German submarines in the North Atlantic were based on the statistical evaluation of the probability of success-the results proved the validity of the statistical approach. The decision to use mass air attacks over the continent of Europe was made on a similar basis. The strategy employed in attacking Japanese shipping was founded upon the same principle. This whole subject and some of its possible applications to peacetime operations are described by Kittel (Sciencr,February 7 , 1947 1. 943
