Search

This paper addresses the problem of defining numerical operations on a relational database to accommodate the statistical analyses associated with a bivariate frequency table. An attempt has been made to extend Codd's relational algebra to include simple bivariate statistical operations preserving the closure of Codd's algebra. This extended algebra is applied to bivariate relational data structures needed for real-time automatic statistical quality control of a manufacturing process. We also discuss some new category-numeric operations on relational tables. [ABSTRACT FROM AUTHOR]

This paper extends Codd's relational view to represent statistical data and to achieve the efficient analysis of statistical data. It discusses why the relational calculus has not been popular with statisticians. A new view called a statistical relational table is presented, to meet the needs of the statisticians. Some of Codd's relational operators are extended to the statistical relational tables. New operators, based on the statistical relational tables, are introduced for communicating requests for statistical analysis. A new query language, called the query-by-statistical-relational-table (which has some similarities with query-by-example), is introduced. Extensions of SQL language for processing the commands of the new query language are also discussed. Creation and storage of metadata for fast statistical analysis are considered. Some problems related to privacy in statistical databases are also examined. [ABSTRACT FROM AUTHOR]

This paper discusses some applications of statistical and database techniques for integrating tests in manufacturing products. It shows how statistical databases can be used for automatically controlling a manufacturing process in real time. Some new statistical methods of manufacturing testing, e.g., test-compression, testing-by- sampling, testing-by-factorial-design, are discussed. All these techniques are possible because of the availability of a statistical database. [ABSTRACT FROM AUTHOR]

In this paper, we will present sampling theory pertinent to the following type of sample design. Each one of the B boxes is shaken and classified into one of L strata on the basis of the auditory observation made concerning the quality of the content. A sample of boxes is selected from each stratum, and an accurate observation is made by inspecting the content of each box selected for the sample. The efficiency of this design will depend upon the accuracy of the auditory observation, and also on the costs involved. [ABSTRACT FROM AUTHOR]