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master's thesis
Primjena statističkih metoda u predviđanju prodaje
Zagreb: University of Zagreb, Faculty of Science, 2017. urn:nbn:hr:217:189000
Šutalo, Karla
University of Zagreb
Faculty of Science
Department of Mathematics

Institutional repository: Repository of the Faculty of Science

Cite this document

Šutalo, K. (2017). Primjena statističkih metoda u predviđanju prodaje (Master's thesis). Zagreb: University of Zagreb, Faculty of Science. Retrieved from https://urn.nsk.hr/urn:nbn:hr:217:189000

Šutalo, Karla. "Primjena statističkih metoda u predviđanju prodaje." Master's thesis, University of Zagreb, Faculty of Science, 2017. https://urn.nsk.hr/urn:nbn:hr:217:189000

Šutalo, Karla. "Primjena statističkih metoda u predviđanju prodaje." Master's thesis, University of Zagreb, Faculty of Science, 2017. https://urn.nsk.hr/urn:nbn:hr:217:189000

Šutalo, K. (2017). 'Primjena statističkih metoda u predviđanju prodaje', Master's thesis, University of Zagreb, Faculty of Science, accessed 23 December 2024, https://urn.nsk.hr/urn:nbn:hr:217:189000

Šutalo K. Primjena statističkih metoda u predviđanju prodaje [Master's thesis]. Zagreb: University of Zagreb, Faculty of Science; 2017 [cited 2024 December 23] Available at: https://urn.nsk.hr/urn:nbn:hr:217:189000

K. Šutalo, "Primjena statističkih metoda u predviđanju prodaje", Master's thesis, University of Zagreb, Faculty of Science, Zagreb, 2017. Available at: https://urn.nsk.hr/urn:nbn:hr:217:189000

Metadata
TitlePrimjena statističkih metoda u predviđanju prodaje
AuthorKarla Šutalo
MentorSiniša Slijepčević (mentor)
Committee memberSiniša Slijepčević (predsjednik povjerenstva)
Committee memberIlja Gogić (član povjerenstva)
Committee memberIgor Pažanin (član povjerenstva)
Committee memberZvonimir Tutek (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Science
(Department of Mathematics)
Zagreb
Defense date and country2017-09-28, Croatia
Scientific / art field,
discipline and subdiscipline		NATURAL SCIENCES
Mathematics
Abstract
Cilj ovog rada je naći model koji najbolje opisuje podatke o prodaji grupe proizvoda i napraviti predviđanje buduće prodaje. Podaci o prodaji su vremenski niz za koji definiramo najvažnije pojmove: stacionarnost, autokovarijacijsku i autokorelacijsku funkciju. Kod modeliranja podataka koristimo teoriju vezanu uz stacionarne procese pa opisujemo metode uklanjanja trenda i sezonalnosti iz podataka kako bi dobili stacionaran niz koji dalje modeliramo. Definiramo ARMA procese, odnosno autoregresivne procese pomičnih prosjeka i navodimo neka njihova važna svojstva. Obrađenu teoriju primjenjujemo na stvarnim podacima o prodaji grupe proizvoda, gdje dio podataka modeliramo ARMA procesom i predviđamo njihovu prodaju. Na kraju dobiveno predviđanje uspoređujemo sa stvarnim podacima o prodaji i zaključujemo kako ARMA proces daje dosta dobra predviđanja prodaje.
Abstract (english)
The goal of this thesis was to develop a model which describes the sales data for the group of three products and predicts group’s future sales. Sales data is time series for which we define the most important terms: stationarity followed by autocovariance and autocorrelation function. Using theoretical knowledge we defined statistical methods for removing trend and seasonal component from the time series which then leaves us with stationary time series used for modeling. We defined ARMA process, which stands for the Autoregressive-moving-average process, and define some of its properties. We applied theoretical knowledge on actual sales data for the product group by developing an ARMA model on data sample and predicting future sales. Finally, we compared predicted future sales with realized sales and came to the conclusion that ARMA process describes our data well and gives good sales prediction.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:217:189000
Study programmeTitle: Finance and Business Mathematics
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 In copyright icon
Created on2018-04-27 13:14:07