Distribution Laws of Small Size Samples. Metrological Implementation

Author

Florescu, Radu ; Thirer, Nonel

Author_Institution

Dept. of Electr. & Electron. Eng., ORT Braude Coll., Karmiel

fYear

2006

Firstpage

79

Lastpage

81

Abstract

In this paper is exposed an original technique to determine the empirical probability density function (pdf) and the empirical cumulative distribution function (cdf) and to estimate moments of any order, for a small size random sample (m=3 - 10) of a continuous random variable (rv). The efficiency of the proposed method is checked up by applying the Kolmogorov-Smirnov test to several series of pseudorandom numbers heaving known distribution laws. In the last part of the paper are presented the advantages of our method for distribution determination in metrological measurements, specially for destructive or expensive measurements.

Keywords

measurement theory; probability; sampling methods; Kolmogorov-Smirnov test; continuous random variable; distribution laws; empirical cumulative distribution function; metrological implementation; probability density function; pseudorandom numbers; Biology computing; Data mining; Distributed computing; Distribution functions; Metrology; Phase frequency detector; Probability density function; Random variables; Statistical distributions; Testing; Consistent and unbiased estimators; Kolmogorov-Smirnov test; Metrological measurements; Pseudorandom numbers; Random small size sample;

fLanguage

English

Publisher

ieee

Conference_Titel

Electrical and Electronics Engineers in Israel, 2006 IEEE 24th Convention of

Conference_Location

Eilat

Print_ISBN

1-4244-0229-8

Electronic_ISBN

1-4244-0230-1

Type

conf

DOI

10.1109/EEEI.2006.321099

Filename

4115250