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- W2360698749 abstract "The scientist often is faced with the problem of designing an experiment which has as its goal the determination of conditions which will maximize the mean value of some response. For example, a metallurgist may wish to determine which of several types of alloys will produce the highest mean tensile strength, an ordnance engineer may wish to determine which of several lots of projectiles will produce the longest mean range, or an agronomist may wish to determine which of several varieties of grain will produce the highest mean yield. All of the above problems are alike in the following important respect: the factor under consideration (type of alloy, lot of projectiles, variety of grain) is qualitative. They are to be differentiated from problems in which the factor under consideration is quantitative. (If the agronomist wished to determine for a given variety of grain which rate of application of a particular fertilizer will produce the highest mean yield, then the factor under consideration is quantitative.) In multifactor experiments it is possible to have various combinations of qualitative and quantitative factors. For example, in two-factor experiments both of the factors can be qualitative, one can be qualitative and one quantitative, or both can be quantitative. In general, in a p-factor experiment, p + 1 combinations are possible." @default.
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- W2360698749 date "1958-09-01" @default.
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- W2360698749 title "A Sequential Multiple-Decision Procedure for Selecting the Best One of Several Normal Populations with a Common Unknown Variance, and Its Use with Various Experimental Designs" @default.
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- W2360698749 doi "https://doi.org/10.2307/2527883" @default.
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