Statistical methods for dividing sites into recommendation domains on the basis of experimental results

dc.creatorMead, R.
dc.date2012-01-06T05:06:18Z
dc.date2012-01-06T05:06:18Z
dc.date[1990?]
dc.date.accessioned2023-07-17T19:55:15Z
dc.date.available2023-07-17T19:55:15Z
dc.identifierhttp://hdl.handle.net/10883/866
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/7508195
dc.descriptionThe purpose of identifying recommendation domains; must be for making recommendations from current data and for planning and interpreting future experiments. In a general sense every applied scientist must have a concept of a recommendation domain for his/her research. Some concept of the population to which results are relevant is integral to any research (even statistics!). The data on which the division of sites into groups for potential domains maybe some combination of (I) economic/sociological: based usually on surveys: (2) physical/meteorological/soils/vegetation: based on observation or on records from nearby available sources; (3) experimental results. There is also always potential for general qualitative judgment about site similarities. There are two stages to the identification of domains, which is a dynamic process rather than a permanent decision. We should separate the process of constructing groups from that of testing, or validating the group structure. The group construction may be attempted using any of the three forms of data. The validation process appears (to me) to be peculiar to experimental data because that data carries with it information about the precision of estimates calculated from the data. It would, of course, be possible to use the precision information inherent in experimental data to test groups (i.e. tentative domains) derived from other forms of data.
dc.description41 pages
dc.formatPDF
dc.languageEnglish
dc.publisherCIMMYT
dc.relationCIMMYT Training Working Document
dc.rightsCIMMYT manages Intellectual Assets as International Public Goods. The user is free to download, print, store and share this work. In case you want to translate or create any other derivative work and share or distribute such translation/derivative work, please contact CIMMYT-Knowledge-Center@cgiar.org indicating the work you want to use and the kind of use you intend; CIMMYT will contact you with the suitable license for that purpose.
dc.rightsOpen Access
dc.subjectAGRICULTURAL SCIENCES AND BIOTECHNOLOGY
dc.subjectCOMPUTER APPLICATIONS
dc.subjectCROPPING SYSTEMS
dc.subjectDATA ANALYSIS
dc.subjectEXPERIMENTATION
dc.subjectSAMPLING
dc.subjectSPACING
dc.subjectSTATISTICAL METHODS
dc.subjectFARMING SYSTEMS
dc.subjectCOMPUTER APPLICATIONS
dc.subjectCROPPING SYSTEMS
dc.subjectDATA ANALYSIS
dc.subjectEXPERIMENTATION
dc.subjectSAMPLING
dc.subjectSPACING
dc.subjectSTATISTICAL METHODS
dc.subjectFARMING SYSTEMS
dc.titleStatistical methods for dividing sites into recommendation domains on the basis of experimental results
dc.typeBook
dc.coverageMexico


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