magistrsko delo
Lucija Gračner (Author), Dominik Benkovič (Mentor)

Abstract

Statistika kot interdisciplinarna veja matematike obsega številne uporabne metode preučevanja različnih spremenljivk na podlagi realnih, življenjskih primerov. Prednost statističnih metod je predvsem vključenost številnih preiskovanih spremenljivk. Metode preiskovanja so povezane tudi z ostalimi matematičnimi disciplinami, kot so algebra, analiza in geometrija. Osrednji in največkrat uporabljeni pojem je razdalja. Vrednosti razdalje dobimo s pomočjo osnovnih statistik, prikazujemo jih z matrikami in v tabelah. Magistrsko delo je razdeljeno na dva dela. V prvem delu smo opredelili osnovne statistične pojme, uporabnost matrik v statistiki ter osnovne pojme metrike in norme, ki so osnova osrednjega dela magistrskega dela. Razložili smo osnovne statistike, kot so disperzija, aritmetična sredina, varianca in kovarianca, in jih podkrepili z zgledi. Prav tako smo opredelili in z zgledi razložili pojma metrika in norma ter natančneje matrike in vrste metrik glede na statistične osnovne pojme. V drugem delu smo osnovne pojme matematičnih disciplin povezali z zgledi različnih znanih razdalj, s čimer smo dobili boljši vpogled v interdisciplinarnost statistike.

Keywords

magistrsko delo;statistika;multivariantna razdalja;Mahalanobisova razdalja;evklidska razdalja;Penrosova razdalja;

Data

Language: Slovenian
Year of publishing:
Typology: 2.09 - Master's Thesis
Organization: UM FNM - Faculty of Natural Sciences and Mathematics
Publisher: [L. Gračner]
UDC: 519.237(043.2)
COBISS: 70565635 Link will open in a new window
Views: 330
Downloads: 29
Average score: 0 (0 votes)
Metadata: JSON JSON-RDF JSON-LD TURTLE N-TRIPLES XML RDFA MICRODATA DC-XML DC-RDF RDF

Other data

Secondary language: English
Secondary title: Measuring and testing multivariate distances
Secondary abstract: Statistics is as an interdisciplinary branch of mathematics which encompasses useful methods of studying various variables based on real-life examples. The main advantage of statistical methods is the inclusion of many investigated variables. Investigation methods are also related to other mathematical disciplines such as algebra, analysis and geometry. The central and most used term is distance. Distance values are calculated with the basic statistics, and they are shown with matrices and in tables. The master's thesis is composed of two parts. In the first part, we defined the basic statistical concepts and the applicability of matrices in statistics. In addition, we presented basic concepts of metrics and norms, which were the basis of the central part of our thesis. We defined basic statistics such as variance, arithmetic mean, variance, and covariance, and illustrated them with examples. We also defined and explained the concepts of metrics and norm, more precisely matrices and types of metrics according to statistical basic concepts. In the second part of our thesis, we connected the basic concepts of mathematics with examples of various types of distances, thus gaining a better insight into the interdisciplinarity of statistical science.
Secondary keywords: master theses;statistics;multivariate distance;Mahalanobis distance;Euclidean distance;Penrose distance;Matematična statistika;Matrike (matematika);Statistične metode;Razdalje;Univerzitetna in visokošolska dela;
Type (COBISS): Master's thesis/paper
Thesis comment: Univ. v Mariboru, Fak. za naravoslovje in matematiko, Oddelek za matematiko in računalništvo
Pages: 74 f.
ID: 12940024