Titlebook: Breakthroughs in Statistics; Methodology and Dist Samuel Kotz,Norman L. Johnson Textbook 1992 Springer-Verlag New York, Inc. 1992 Outlook.S

偶然

The Arrangement of Field Experiments,sts has been turned to the . of field experiments. During this period, experiments of the uniformity trial type have demonstrated the magnitude and ubiquity of that class of error which cannot be ascribed to carelessness in measuring the land or weighing the produce, and which is consequently descri

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On the Two Different Aspects of the Representative Method: the Method of Stratified Sampling and thd the possibility of practical applications of the representative method has attracted the attention of many statisticians in different countries. Very probably this popularity of the representative method is also partly due to the general crisis, to the scarcity of money and to the necessity of car

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, Wilcoxon (1945) Individual Comparisons by Ranking Methods,on occupy a central place in a newly developing branch of statistics that became known as nonparametrics. Wilcoxon (1892–1965) a physical chemist by training who was employed by the American Cyanamid Company in Stamford, Connecticut, came to statistics because of a need for analyzing laboratory data

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Individual Comparisons by Ranking Methods,o treatments, which are unpaired, or (b) we may have a number of paired comparisons leading to a series of differences, some of which may be positive and some negative. The appropriate methods for testing the significance of the differences of the means in these two cases are described in most of th

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,On Some Useful “Inefficient” Statistics,es require only a counting sorter. The methods proposed are designed especially for situations where data are inexpensive compared to the cost of analysis by means of statistically “efficient” or “most powerful” procedures. The principal technique is the use of functions of order statistics, which w

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, Durbin and Watson (1950, 1951) Testing for Serial Correlation in Least Squares Regression. I, II,herian revolution of the 1920s and 1930s, statistical methods were mainly applied in the natural sciences where one could often design the experiments that produced the data. The emphasis was largely on how the experiments should be designed to make the least-squares assumptions valid rather than on