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master's thesis
Faktorska analiza
Zagreb: University of Zagreb, Faculty of Science, 2024. urn:nbn:hr:217:004859
Magdić, Lucija
University of Zagreb
Faculty of Science
Department of Mathematics

Institutional repository: Repository of the Faculty of Science

Cite this document

Magdić, L. (2024). Faktorska analiza (Master's thesis). Zagreb: University of Zagreb, Faculty of Science. Retrieved from https://urn.nsk.hr/urn:nbn:hr:217:004859

Magdić, Lucija. "Faktorska analiza." Master's thesis, University of Zagreb, Faculty of Science, 2024. https://urn.nsk.hr/urn:nbn:hr:217:004859

Magdić, Lucija. "Faktorska analiza." Master's thesis, University of Zagreb, Faculty of Science, 2024. https://urn.nsk.hr/urn:nbn:hr:217:004859

Magdić, L. (2024). 'Faktorska analiza', Master's thesis, University of Zagreb, Faculty of Science, accessed 16 May 2024, https://urn.nsk.hr/urn:nbn:hr:217:004859

Magdić L. Faktorska analiza [Master's thesis]. Zagreb: University of Zagreb, Faculty of Science; 2024 [cited 2024 May 16] Available at: https://urn.nsk.hr/urn:nbn:hr:217:004859

L. Magdić, "Faktorska analiza", Master's thesis, University of Zagreb, Faculty of Science, Zagreb, 2024. Available at: https://urn.nsk.hr/urn:nbn:hr:217:004859

Metadata
TitleFaktorska analiza
Title (english)Factor analysis
AuthorLucija Magdić
MentorSnježana Lubura Strunjak (mentor)
Committee memberSnježana Lubura Strunjak (predsjednik povjerenstva)
Committee memberNenad Antonić (član povjerenstva)
Committee memberNina Kamčev (član povjerenstva)
Committee memberIvica Nakić (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Science
(Department of Mathematics)
Zagreb
Defense date and country2024-02-28, Croatia
Scientific / art field,
discipline and subdiscipline		NATURAL SCIENCES
Mathematics
Abstract
U ovom diplomskom radu proučavali smo teorijsku pozadinu faktorske analize te njenu primjenu na konkretnom skupu podataka. Faktorska analiza je statistička metoda koja kao cilj ima pronalaženje manjeg broja neopaženih varijabli (faktora) koje objašnjavaju što veći dio varijabilnosti početnog skupa podataka. Početne varijable koje su korelirane tada možemo prikazati kao linearne kombinacije nekoreliranih faktora, iz cijih težina možemo uvidjeti koliki je utjecaj određenog faktora na neku od varijabli. Na samome početku smo definirali faktorski model te objasnili od kojih se sve komponenti sastoji. Zatim smo proučavali razne metode procjene faktora koje su sve imale isti cilj, a to je ekstrakcija maksimalne varijance iz skupa podataka sa svakim faktorom. Kod odabira broja faktora u modelu uvidjeli smo da postoje razni kriteriji pomoću kojih možemo odrediti broj potrebnih faktora, koji su na kraju davali identične rezultate. Nakon što smo došli do rješenje nerijetko je teško interpretirati dobivene rezultate pa smo se u takvim slučajevima oslanjali na rotacije koje su nam olakšale donošenje zaključaka na način da su poboljšavale samu interpretaciju našeg rješenja. Na samome kraju, dali smo tri primjera u kojima smo sproveli faktorsku analizu.
Abstract (english)
In this master’s thesis, we examined the theoretical background of factor analysis and its application to a specific dataset. Factor analysis is a statistical method aimed at finding a smaller number of unobserved variables (factors) that explain a larger portion of the variability in the original dataset. The initial correlated variables can then be represented as linear combinations of uncorrelated factors, from which we can determine the influence of a particular factor on each variable based on their weights. At the outset, we defined the factor model and explained its components. We then explored various factor estimation methods, all with the same goal of extracting maximum variance from the dataset with each factor. When selecting the number of factors in the model, we found various criteria to determine the necessary number of factors, which ultimately yielded identical results. After obtaining the solution, interpreting the results can often be challenging, so in such cases, we relied on rotations to facilitate decision-making by improving the interpretation of our solution. Finally, we provided three examples where we conducted factor analysis.
Keywords
Languagecroatian
URN:NBNurn:nbn:hr:217:004859
Study programmeTitle: Mathematical Statistics
Study programme type: university
Study level: graduate
Academic / professional title: sveučilišni magistar matematike (sveučilišni magistar matematike)
Type of resourceText
File originBorn digital
Access conditionsOpen access
Terms of useLicence In copyright icon
Created on2024-03-13 12:12:30