The Statistical Analysis of the Radioactivity Concentration of the Water Data in Malatya City, Turkey

Author(s):  
Mahmut Doğru ◽  
Mesut Yalçin ◽  
Fatih Külahci ◽  
Cumhur Canbazoğlu ◽  
Oktay Baykara
Symmetry ◽  
2020 ◽  
Vol 12 (8) ◽  
pp. 1219
Author(s):  
Fusun Yalcin ◽  
Sezer Unal ◽  
Mustafa Gurhan Yalcin ◽  
Ozgur Akturk ◽  
Sema Bilge Ocak ◽  
...  

The study aims to investigate the effects of Burdur (Turkey) marble on human health by interpreting their radioactivity concentration (226Ra, 232Th, and 40K), radiological hazard parameters, chemical concentration, physical properties, and all data related to these features by using multivariate statistical methods. Chemical and radionuclide analyses were performed on marble samples. The data were interpreted by statistical analysis. According to the regression model, an increase in the concentration of vanadium carried to the environment by hydrothermal waters causes a 4.452-fold higher concentration of 226Ra. The R2 value of the model was 0.64 and it was statistically significant. The maximum concentration of 226Ra in Isparta Davraz Beige sample (M7) exceeded the values of some countries’ standards. Except for M7, the analyzed sorts of marble can be used safely in dwellings and public buildings.


1966 ◽  
Vol 24 ◽  
pp. 188-189
Author(s):  
T. J. Deeming

If we make a set of measurements, such as narrow-band or multicolour photo-electric measurements, which are designed to improve a scheme of classification, and in particular if they are designed to extend the number of dimensions of classification, i.e. the number of classification parameters, then some important problems of analytical procedure arise. First, it is important not to reproduce the errors of the classification scheme which we are trying to improve. Second, when trying to extend the number of dimensions of classification we have little or nothing with which to test the validity of the new parameters.Problems similar to these have occurred in other areas of scientific research (notably psychology and education) and the branch of Statistics called Multivariate Analysis has been developed to deal with them. The techniques of this subject are largely unknown to astronomers, but, if carefully applied, they should at the very least ensure that the astronomer gets the maximum amount of information out of his data and does not waste his time looking for information which is not there. More optimistically, these techniques are potentially capable of indicating the number of classification parameters necessary and giving specific formulas for computing them, as well as pinpointing those particular measurements which are most crucial for determining the classification parameters.


Author(s):  
Gianluigi Botton ◽  
Gilles L'espérance

As interest for parallel EELS spectrum imaging grows in laboratories equipped with commercial spectrometers, different approaches were used in recent years by a few research groups in the development of the technique of spectrum imaging as reported in the literature. Either by controlling, with a personal computer both the microsope and the spectrometer or using more powerful workstations interfaced to conventional multichannel analysers with commercially available programs to control the microscope and the spectrometer, spectrum images can now be obtained. Work on the limits of the technique, in terms of the quantitative performance was reported, however, by the present author where a systematic study of artifacts detection limits, statistical errors as a function of desired spatial resolution and range of chemical elements to be studied in a map was carried out The aim of the present paper is to show an application of quantitative parallel EELS spectrum imaging where statistical analysis is performed at each pixel and interpretation is carried out using criteria established from the statistical analysis and variations in composition are analyzed with the help of information retreived from t/γ maps so that artifacts are avoided.


2001 ◽  
Vol 6 (3) ◽  
pp. 187-193 ◽  
Author(s):  
John R. Nesselroade

A focus on the study of development and other kinds of changes in the whole individual has been one of the hallmarks of research by Magnusson and his colleagues. A number of different approaches emphasize this individual focus in their respective ways. This presentation focuses on intraindividual variability stemming from Cattell's P-technique factor analytic proposals, making several refinements to make it more tractable from a research design standpoint and more appropriate from a statistical analysis perspective. The associated methods make it possible to study intraindividual variability both within and between individuals. An empirical example is used to illustrate the procedure.


1967 ◽  
Vol 12 (9) ◽  
pp. 467-467
Author(s):  
JOHN C. LOEHLIN
Keyword(s):  

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