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master's thesis
Primjena linearne regresije na predviđanje COVID-19 pandemije
Zagreb: University of Zagreb, Faculty of Science, 2022. urn:nbn:hr:217:073818
Matić, Nikolina
University of Zagreb
Faculty of Science
Department of Mathematics

Institutional repository: Repository of the Faculty of Science

Cite this document

Matić, N. (2022). Primjena linearne regresije na predviđanje COVID-19 pandemije (Master's thesis). Zagreb: University of Zagreb, Faculty of Science. Retrieved from https://urn.nsk.hr/urn:nbn:hr:217:073818

Matić, Nikolina. "Primjena linearne regresije na predviđanje COVID-19 pandemije." Master's thesis, University of Zagreb, Faculty of Science, 2022. https://urn.nsk.hr/urn:nbn:hr:217:073818

Matić, Nikolina. "Primjena linearne regresije na predviđanje COVID-19 pandemije." Master's thesis, University of Zagreb, Faculty of Science, 2022. https://urn.nsk.hr/urn:nbn:hr:217:073818

Matić, N. (2022). 'Primjena linearne regresije na predviđanje COVID-19 pandemije', Master's thesis, University of Zagreb, Faculty of Science, accessed 27 December 2024, https://urn.nsk.hr/urn:nbn:hr:217:073818

Matić N. Primjena linearne regresije na predviđanje COVID-19 pandemije [Master's thesis]. Zagreb: University of Zagreb, Faculty of Science; 2022 [cited 2024 December 27] Available at: https://urn.nsk.hr/urn:nbn:hr:217:073818

N. Matić, "Primjena linearne regresije na predviđanje COVID-19 pandemije", Master's thesis, University of Zagreb, Faculty of Science, Zagreb, 2022. Available at: https://urn.nsk.hr/urn:nbn:hr:217:073818

Metadata
TitlePrimjena linearne regresije na predviđanje COVID-19 pandemije
Title (english)Application of linear regression to COVID-19 pandemic prediction
AuthorNikolina Matić
MentorSiniša Slijepčević (mentor)
Committee memberSiniša Slijepčević (predsjednik povjerenstva)
Committee memberDražen Adamović (član povjerenstva)
Committee memberRudi Mrazović (član povjerenstva)
Committee memberIvica Nakić (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Science
(Department of Mathematics)
Zagreb
Defense date and country2022-05-05, Croatia
Scientific / art field,
discipline and subdiscipline		NATURAL SCIENCES
Mathematics
Abstract
U ovom radu, objašnjavamo teorijsku pozadinu linearne regresije te primjenjujemo statistički model regresije na stvarne podatke. U prvom poglavlju iskazana je matematička teorija potrebna za razumijevanje sadržaja rada. Drugo poglavlje opisuje model jednostavne linearne regresije te model višestruke linearne regresije. Opisani su uvjeti koje proučavani podaci moraju zadovoljavati kako bi konstrukcija regresijskog modela bila smislena. Konačno, u trećem poglavlju, primijenjujemo linearnu regresiju na aktualnu tematiku današnjice, COVID-19 pandemiju. Sama analiza uključivala je 22 različita faktora (nezavisne varijable) promatrana u 99 različitih zemalja, a promatrani podaci opisuju tjedni ukupan broj oboljelih i smrtnih slučajeva. Same varijable opisuju uređenost pojedine zemlje te one nisu posljedica pojavljivanja COVID-19 pandemije, već one definiraju demografsko-geografsku, političkozakonsku, socijalno-ekonomsku i zdrastvenu sliku pojedine zemlje.
Abstract (english)
This work discusses the theoretical background of linear regression and application of statistical regression model with real data. In the first chapter mathematical theory is stated, required for understanding the work itself. The second chapter describes the simple linear regression model as well as the multiple linear regression model. Various conditions are described which the examined data must satisfy in order for the construction to be meaningful. Finally, in the third chapter, linear regression is being applied on a trending topic of today, the COVID-19 pandemic. The very analysis includes 22 different factors (independent variables) observed in 99 different states, whereas recorded data describes the total number of infected and death cases per week. The variables themselves describe the structure of the individual state and they are not the consequence of occurrences from COVID-19 pandemic, but they define demographic-geographical, political-legal, socioeconomic and health aspects of the individual state.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:217:073818
Study programmeTitle: Mathematics Education; specializations in: Mathematics Education
Course: Mathematics Education
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra edukacije matematike (magistar/magistra edukacije matematike)
Type of resourceText
File originBorn digital
Access conditionsOpen access
Terms of useLicence In copyright icon
Created on2022-06-07 11:20:42