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master's thesis
Primjena logističke regresije u modeliranju vjernosti posjetitelja
2022. urn:nbn:hr:166:949959
Zovko, Mila
University of Split
Faculty of Science
Department of Mathematics

Cite this document

Zovko, M. (2022). Primjena logističke regresije u modeliranju vjernosti posjetitelja (Master's thesis). Split: University of Split, Faculty of Science. Retrieved from https://urn.nsk.hr/urn:nbn:hr:166:949959

Zovko, Mila. "Primjena logističke regresije u modeliranju vjernosti posjetitelja." Master's thesis, University of Split, Faculty of Science, 2022. https://urn.nsk.hr/urn:nbn:hr:166:949959

Zovko, Mila. "Primjena logističke regresije u modeliranju vjernosti posjetitelja." Master's thesis, University of Split, Faculty of Science, 2022. https://urn.nsk.hr/urn:nbn:hr:166:949959

Zovko, M. (2022). 'Primjena logističke regresije u modeliranju vjernosti posjetitelja', Master's thesis, University of Split, Faculty of Science, accessed 14 November 2024, https://urn.nsk.hr/urn:nbn:hr:166:949959

Zovko M. Primjena logističke regresije u modeliranju vjernosti posjetitelja [Master's thesis]. Split: University of Split, Faculty of Science; 2022 [cited 2024 November 14] Available at: https://urn.nsk.hr/urn:nbn:hr:166:949959

M. Zovko, "Primjena logističke regresije u modeliranju vjernosti posjetitelja", Master's thesis, University of Split, Faculty of Science, Split, 2022. Available at: https://urn.nsk.hr/urn:nbn:hr:166:949959

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Metadata
TitlePrimjena logističke regresije u modeliranju vjernosti posjetitelja
Title (english)The application of logistic regression in modelling visitor loyalty
AuthorMila Zovko
MentorTea Martinić Bilać (mentor)
MentorAna Perišić (pomoć pri izradi, neposredni voditelj)
Committee memberTea Martinić Bilać (predsjednik povjerenstva)
Committee memberAna Laštre (član povjerenstva)
Committee memberAna Perišić (član povjerenstva)
GranterUniversity of Split
Faculty of Science
(Department of Mathematics)
Split
Defense date and country2022-09-26, Croatia
Scientific / art field,
discipline and subdiscipline		NATURAL SCIENCES
Mathematics
Abstract
Logička regresija analizira odnos izmedu dihotomne zavisne varijable i jedne ili više nezavisnih varijabli. Najčešće se koristi u prediktivnom modeliranju, gdje model procjenjuje vjerojatnost kategorija u klasifikacijskim problemima. U prvom dijelu rada koji se odnosi na teorijsku podlogu logističke regresije upoznajemo se sa familijom generaliziranih linearnih modela. Zatim, izvodimo pripadajući univarijatni i multivarijatni logistički model, metodom maksimalne vjerodostojnosti procijenjujemo njihove parametre, testiramo značajnost parametara te objašnjavamo interpretaciju modela. U drugom dijelu prikazujemo primjenu logističke regresije u modeliranju vjernosti posjetitelja gdje ispitujemo možemo li vjernost posjetitelja predvidjeti na temelju njihovog zadovoljstva, te u svrhu prikaza izgradnje modela sa različitim vrstama varijabli, vjernost modeliramo i uz jednu kategorijalnu varijablu koja se odnosi na zemlju porijekla posjetitelja.
Abstract (english)
Logistic regression is used to examine the association of one dichotomous variable with one or more independent variables. It is extensively used in predictive modeling, where the model estimates probabilities for classification problems with two possible outcomes. The first part of the thesis refers to the theoretical foundation of logistic regression. In this part, generalised linear models are introduced, which is followed by the theoretical background of univariate and multivariate logistic regression modelling. We present the method of maximum likelihood parameter estimation, significance testing and explain the interpretation of the model. In the second part of the thesis, we present the application of logistic regression in visitor loyalty modeling. We perform logistic regression in order to examine whether visitor loyalty can be predicted by visitor satisfaction. Also, to present the model building with different types of variables, loyalty is modeled with one categorical variable referring to the country of origin.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:166:949959
Study programmeTitle: Mathematics; specializations in: major in pure mathematics, major in computing, major in teaching, major in statistics and computing
Course: major in statistics and computing
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra matematike (magistar/magistra matematike)
Type of resourceText
File originBorn digital
Access conditionsOpen access
Terms of useLicence Attribution 4.0 International (CC BY 4.0) icon
Created on2023-01-31 12:13:30