J. Choobineh, Dept. of Bus. Anal. & Res., Texas A&M Univ., College Station, TX, USA
A. Kini, Dept. of Bus. Anal. & Res., Texas A&M Univ., College Station, TX, USA
Statistical modeling and analysis is extensively used in businesses for various purposes including graphic visualization of data, measurement of central tendencies and other statistics, and inferences on populations based on samples. Data is the fundamental component of each of these activities. In this paper an extension of the standard database language SQL for statistical modeling and analysis is presented. Models covered include descriptive analytic and graphic measures, discrete probability distributions, continuous probability distributions, inferential statistics, and regression analysis. Through the use of SQLSAM, seamless integration of existing data in organizations' databases and their statistical analysis can be achieved.
Index Terms:
statistical analysis; statistical databases; business data processing; data visualisation; query languages; probability; decision support systems; statistical analysis; statistical modeling; SQLSAM; SQL; business; graphic visualization; statistics; inferences; standard database language; discrete probability distributions; continuous probability distributions; inferential statistics; regression analysis; organization databases; business decision making
Citation:
J. Choobineh, A. Kini, "SQLSAM: SQL for statistical analysis and modeling," hicss, pp.418, 28th Hawaii International Conference on System Sciences (HICSS'95), 1995
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