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Statistical methods for food and agriculture
318 A number of runs with different labor and capital supplies were made in order to examine the magnitude of the objective function and to identify the main properties of the regional agricultural production function, resource utilization, regional specialization, production bottlenecks, production capacities, etc. Numerical quantities are shown by subregion and producer types (private, cooperative, and state) for area and volume of crops, number of livestock, and uses of crops (fed to livestock, used for humans or sold). Specialization was denoted for producer types with state farms emphasizing wheat and private farms emphasizing sugar beets due to their relatively large labor supply. In general, the results were found to be in agreement with expectations of planners and decision makers of the region. The authors conclude that GRAM can be used in the role of an independent planning and policy tool, but with potential linkages with other systems. Another important conclusion was that the model could be run on a relatively small computer. As with most other IIASA models, no information is provided on the source, nature, form, and quality of the data. We have no notion of how the data biased or strengthened the results. A rather large number of regional and interregional programming models similar in nature have been applied and solved over the world. The study cites mainly IIASA references and few of the regional programming models solved in the past. E.O. HEADY (The Center for Agricultural and Rural Development Iowa State University of Science and Technology 578 East Hall Ames, IA 50010 U.S.A.)
STATISTICAL METHODS Statistical M e t h o d s f o r F o o d and Agriculture. F.E. Bender, L.W. Douglas and
A. Kramer, Avi, Westport, CT, U.S.A., 1982, vii + 345 pp., 119 tables, 55 figs., US $ 25.00, ISBN 0-87055-391-7. "Statistics is a relatively recent development for science and business", say the authors in starting their book, described as an attempt to face two needs: research and business. The first part is an introduction (four chapters) giving a clear definition of statistics and their use, defining the objects, and presenting the probability theory and sampling from a normal distribution, in only 60 pages! Part two on statistics in research includes seven chapters on: several simple problems dealing with two sample comparisons; the concepts of experimental design in comparative experiments; the technique known as the analysis of variance (ANOVA), firstly the one-way ANOVA, and then an extension to designs with more than one source of variation (two chapters);
319 factorial experiments (definition and use); the analysis of covariance, presented at this point under an intuitive approach; and the introduction of the chi-square distribution. In part three, statistics are applied in business and research. The regression analysis, presented as an extremely versatile tool, is examined firstly in its linear form. For correlation analysis, specific attention is devoted to its correct use. Non-parametric statistics and three rank tests are presented, with a short development on the Chebyshev's inequality (a useful distribution-free procedure). The last part, specific to business~ involves chapters on: a presentation of the technique known as evolutionary operations; index numbers, a c o m m o n factor of everyday life, the purpose of which is to construct single statistics; time series, which are very c o m m o n in business and economic statistics. The analysis provides a technique for working with data which occur as unique points. This chapter develops some considerations on the simple structure used to decompose observed variation (trend, seasonal, cyclical and error); control charts, the development of which is a major contribution to management; and using computers in statistical analysis. The Appendix (17 pp.) is a source of diversified information: from areas under the standard normal curve, and the distribution of t, to tables of conversion (including volume of table or teaspoon!). Every chapter is concluded with problems (not solved), references, and suggested reading, and sometimes with a summary. P. JACQUARD (Centre National de la Recherche Scientifique B.P. 5051, Route de Mende
34033 Montpellier (H$rault), France)
STATISTICAL METHODS Statistical M e t h o d s f o r F o o d and Agriculture. F.E. Bender, L.W. Douglas and
A. Kramer, Avi, Westport, CT, U.S.A., 1982, vii + 345 pp., 119 tables, 55 figs., US $ 25.00, ISBN 0-87055-391-7. "Statistics is a relatively recent development for science and business", say the authors in starting their book, described as an attempt to face two needs: research and business. The first part is an introduction (four chapters) giving a clear definition of statistics and their use, defining the objects, and presenting the probability theory and sampling from a normal distribution, in only 60 pages! Part two on statistics in research includes seven chapters on: several simple problems dealing with two sample comparisons; the concepts of experimental design in comparative experiments; the technique known as the analysis of variance (ANOVA), firstly the one-way ANOVA, and then an extension to designs with more than one source of variation (two chapters);
319 factorial experiments (definition and use); the analysis of covariance, presented at this point under an intuitive approach; and the introduction of the chi-square distribution. In part three, statistics are applied in business and research. The regression analysis, presented as an extremely versatile tool, is examined firstly in its linear form. For correlation analysis, specific attention is devoted to its correct use. Non-parametric statistics and three rank tests are presented, with a short development on the Chebyshev's inequality (a useful distribution-free procedure). The last part, specific to business~ involves chapters on: a presentation of the technique known as evolutionary operations; index numbers, a c o m m o n factor of everyday life, the purpose of which is to construct single statistics; time series, which are very c o m m o n in business and economic statistics. The analysis provides a technique for working with data which occur as unique points. This chapter develops some considerations on the simple structure used to decompose observed variation (trend, seasonal, cyclical and error); control charts, the development of which is a major contribution to management; and using computers in statistical analysis. The Appendix (17 pp.) is a source of diversified information: from areas under the standard normal curve, and the distribution of t, to tables of conversion (including volume of table or teaspoon!). Every chapter is concluded with problems (not solved), references, and suggested reading, and sometimes with a summary. P. JACQUARD (Centre National de la Recherche Scientifique B.P. 5051, Route de Mende
34033 Montpellier (H$rault), France)