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undergraduate thesis
Mjere zavisnosti-svojstva i zamke
Osijek: Josip Juraj Strossmayer University of Osijek, Department of Mathematics, 2021. urn:nbn:hr:126:297065
Lamot, Lorena
Josip Juraj Strossmayer University of Osijek
Department of Mathematics
Chair of Pure Mathematics and Mathematics Teaching
Probability, Mathematical Statistics and Data Science Research Group

Institutional repository: Repository of School of Applied Mathematics and Informatics

Cite this document

Lamot, L. (2021). Mjere zavisnosti-svojstva i zamke (Undergraduate thesis). Osijek: Josip Juraj Strossmayer University of Osijek, Department of Mathematics. Retrieved from https://urn.nsk.hr/urn:nbn:hr:126:297065

Lamot, Lorena. "Mjere zavisnosti-svojstva i zamke." Undergraduate thesis, Josip Juraj Strossmayer University of Osijek, Department of Mathematics, 2021. https://urn.nsk.hr/urn:nbn:hr:126:297065

Lamot, Lorena. "Mjere zavisnosti-svojstva i zamke." Undergraduate thesis, Josip Juraj Strossmayer University of Osijek, Department of Mathematics, 2021. https://urn.nsk.hr/urn:nbn:hr:126:297065

Lamot, L. (2021). 'Mjere zavisnosti-svojstva i zamke', Undergraduate thesis, Josip Juraj Strossmayer University of Osijek, Department of Mathematics, accessed 21 March 2025, https://urn.nsk.hr/urn:nbn:hr:126:297065

Lamot L. Mjere zavisnosti-svojstva i zamke [Undergraduate thesis]. Osijek: Josip Juraj Strossmayer University of Osijek, Department of Mathematics; 2021 [cited 2025 March 21] Available at: https://urn.nsk.hr/urn:nbn:hr:126:297065

L. Lamot, "Mjere zavisnosti-svojstva i zamke", Undergraduate thesis, Josip Juraj Strossmayer University of Osijek, Department of Mathematics, Osijek, 2021. Available at: https://urn.nsk.hr/urn:nbn:hr:126:297065

Metadata
TitleMjere zavisnosti-svojstva i zamke
Title (english)Dependency Measures-Properties and Drawbacks
AuthorLorena Lamot
MentorNenad Šuvak (mentor)
GranterJosip Juraj Strossmayer University of Osijek
Department of Mathematics
(Chair of Pure Mathematics and Mathematics Teaching)
(Probability, Mathematical Statistics and Data Science Research Group)
Osijek
Defense date and country2021-09-15, Croatia
Scientific / art field,
discipline and subdiscipline		NATURAL SCIENCES
Mathematics
Probability Theory and Statistics
Abstract
U ovom ćemo se radu baviti mjerama povezanosti dviju slučajnih varijabli. Najprije ćemo uvesti definicije osnovnih numeričkih karakteristika slučajnog vektora koje su nam potrebne za definiranje koeficijenta korelacije. Zatim ćemo detaljno opisati Pearsonov korelacijski koeficijent koji nam daje informaciju o "jakosti" linearne veze između dvije varijable. Navest ćemo njegovu definiciju, svojstva te pretpostavke za njegovo korištenje. Nakon toga ćemo definirati dvije neparametarske mjere asocijacije - Spearmanov koeficijent korelacije ranga te Kendallov τ . Opisat ćemo njihova svojstva i vidjeti njihovu primjenu kroz nekoliko primjera.
Abstract (english)
In this bachelor’s thesis we will be studying measures of correlation or association between two variables. First of all, we will introduce some definitions of basic numerical characteristics of random vector that we need for defying correlation coefficient. After that, we will describe Pearson’s correlation coefficient which gives us information about the strength of linear relationship between two variables. We will define Pearson’s correlation coefficient, say something about its properties and assumptions for its usage. After that, we will define two non-parametric measures of association - Spearman’s rank-order correlation coefficient and Kendall’s τ . We will describe their properties and see their usage on few examples.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:126:297065
Study programmeTitle: University undergraduate study programme in mathematics
Study programme type: university
Study level: undergraduate
Academic / professional title: sveučilišni/a prvostupnik/prvostupnica (baccalaureus/baccalaurea) matematike (sveučilišni/a prvostupnik/prvostupnica (baccalaureus/baccalaurea) matematike)
Type of resourceText
File originBorn digital
Access conditionsOpen access
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Created on2021-10-04 07:00:55