Skip to the main content

Journal of computing and information technology, Vol. 4 No. 4, 1996.

Original scientific paper

Statistics with Non-Precise Data

Reinhard Viertl ; Department of Statistics and Probability Theory, Vienna University of Technology, Wien, Austria

Full text: english pdf 3.602 Kb

page 215-224

downloads: 313

cite

Abstract

In statistical analysis data are usually assumed to be numbers or vectors. But real measurement data of continuous quantities are not precise numbers but more or less non-precise. This imprecision is different from measurement errors and is also called fuzziness. Before analysing the data it is necessary to describe the imprecision of measurements quantitatively. This can be done using the concepts of fuzzy numbers and fuzzy vectors. Then stati stical inference procedures are generalized to the more realistic situation of non-precise data.

Keywords

Data Analysis; Fuzzy Data; Fuzzy Numbers; Non-Precise Data; Statistics

Hrčak ID:

150275

URI

https://hrcak.srce.hr/150275

Publication date:

30.12.1996.

Visits: 837 *