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Title:Korelacijska analiza
Authors:ID Zemljak, Dejan (Author)
ID Benkovič, Dominik (Mentor) More about this mentor... New window
Files:.pdf MAG_Zemljak_Dejan_2019.pdf (500,92 KB)
MD5: AA97A94AC0F342717A8E770400DC7D28
PID: 20.500.12556/dkum/99967ff8-a89a-49f6-8029-8c18e4bfa5fc
 
Language:Slovenian
Work type:Master's thesis/paper
Typology:2.09 - Master's Thesis
Organization:FNM - Faculty of Natural Sciences and Mathematics
Abstract:Magistrsko delo obravnava področje statistike, ki se ukvarja z medsebojno povezanostjo statističnih spremenljivk (korelacijska analiza). Na začetku so podrobno predstavljeni osnovni pojmi, vrste korelacije in funkcijska odvisnost, ki je ključna za dobro razumevanje korelacijske odvisnosti. Za boljše razumevanje korelacijske odvisnosti spremenljivk uporabimo razsevni diagram, s pomočjo katerega predstavimo nekatere najznačilnejše vrste korelacij. V nadaljevanju je izpostavljena jakost linearne korelacije in nekaj namenov uporabe korelacije. Sledi podrobnejša razlaga in predstavitev najpomembnejših lastnosti matematičnega upanja, kovariance, variance in standardnega odklona. Omenjene številske karakteristike so ključne za razumevanje Pearsonovega koeficienta korelacije. Pri Pearsonovem koeficientu korelacije je izpostavljeno, kakšne so njegove lastnosti in povezanosti. Pri omenjenem koeficientu so predstavljeni ocenjevanje in testiranje ter interval zaupanja. Ker imajo na izračun korelacijskega koeficienta velikokrat vpliv druge spremenljivke, ki jih želimo velikokrat izločiti, sta v delu obravnavani tudi parcialna in multipla korelacija. Pri korelacijski analizi je smiselno izpostaviti še Spearmanovo korelacijo rangov, ki je predstavljena v drugem delu magistrskega dela. Predstavljeno je tudi neparametrično testiranje nekolinearnosti. Magistrsko delo se zaključuje s predstavitvijo najpomembnejših posebnih korelacijskih koeficientov. Predstavljeno teorijo dopolnjujejo različni zgledi.
Keywords:korelacijska analiza, korelacijska odvisnost, Pearsonov koeficient korelacije, parcialna korelacija, multipla korelacija, Spearmanova korelacija rangov, posebni koeficienti korelacije
Place of publishing:Maribor
Publisher:[D. Zemljak]
Year of publishing:2019
PID:20.500.12556/DKUM-74003 New window
UDC:519.233.5(043.2)
COBISS.SI-ID:24868616 New window
NUK URN:URN:SI:UM:DK:TJJQKBO4
Publication date in DKUM:05.11.2019
Views:3357
Downloads:541
Metadata:XML DC-XML DC-RDF
Categories:FNM
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Licences

License:CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
Link:http://creativecommons.org/licenses/by-nc-nd/4.0/
Description:The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.
Licensing start date:17.07.2019

Secondary language

Language:English
Title:Correlation analysis
Abstract:The master’s thesis deals with the field of statistics, which studies the interdependence of statistical variables (correlation analysis). In the beginning, the basic concepts, the types of correlation and functional dependency, which is key for a thorough understanding of the correlation dependency, are presented. To better understand the correlation dependency of the variables, a scatterplot is used with the help of which some of the most common types of correlations are presented. Furthermore, the strength of the linear correlation and some of its uses are highlighted. A more detailed explanation and presentation of the most important features, such as mathematical hope, covariance, variance and standard deviation follow. These numerical characteristics are crucial for the understanding of the Pearson’s correlation coefficient. Regarding the Pearson’s correlation coefficient, the focus lies on its properties and relationships. For this coefficient evaluation, testing and the confidence interval are presented. Since the calculation of the correlation coefficient is often influenced by other variables, which should often be excluded, partial and multiple correlation are also considered in the thesis. Regarding the correlation analysis, it is worthwhile to point out Spearman’s rank correlation, which is presented in the second part of the master’s thesis. A non-parametric test of non-linearity is also presented. The master’s thesis concludes with the presentation of the most important special correlation coefficients. The presented theory is complemented by various examples.
Keywords:correlation analysis, correlation dependence, Pearson’s correlation coefficient, partial correlation, multiple correlation, Spearman’s rank correlation, special correlation coefficients


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