Mathematical Sciences: Inferences Concerning the Mean of    Negative Binomial Populations
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{'SignBlockName': 'Bernard McDonald', 'PO_EMAI': None, 'PO_PHON': None}
This research aims at developing an extensive collection of                statistical estimates and hypotheses testing procedures for data                generated by the negative binomial distribution.  The types of                  estimates and testing procedures to be developed are, for the                   most part, analogous to those that exist for data generated by a                normal distribution.  This work is made possible by the existence               of inexpensive computational power.                                                  This research will produce the statistical methodology                     appropriate for analyzing many types of "counting" data                         including, for example, automobile accidents, communication                     failures, and a changing population's size.  The standard                       practice for analyzing these data is to use mathematical                        approximations that are only valid as the number of items studied               goes to infinity.  The impact of this research will be to provide               a collection of accurate statistical tools so that these                        approximations need not be relied upon.
{'FirstName': 'Linda', 'LastName': 'Young', 'PI_MID_INIT': 'J', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Linda J Young', 'EmailAddress': 'LJYoung@ufl.edu', 'NSF_ID': '000371390', 'StartDate': '07/01/1988', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
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{'Code': '9120', 'Text': 'CROSS-DIRECTORATE PROGRAMS'}
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