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Inferential Statistics Methods and the Computer-Based Approach to Project Management


Dukić, Gordana; Sesar, Mate; Sesar, Ivana
Inferential Statistics Methods and the Computer-Based Approach to Project Management // Proceedings of the 13th World Multi-Conference on Systemics, Cybernetics and Informatics (WMSCI 2009) / Callaos, Nagib ; Chu, Hsing-Wei ; Lesso, William ; Tzeng, Jang-Ruey ; Zinn, C. Dale (ur.).
Orlando: International Institute of Informatics and Systemics, 2009. str. 46-51 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)


Naslov
Inferential Statistics Methods and the Computer-Based Approach to Project Management

Autori
Dukić, Gordana ; Sesar, Mate ; Sesar, Ivana

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
Proceedings of the 13th World Multi-Conference on Systemics, Cybernetics and Informatics (WMSCI 2009) / Callaos, Nagib ; Chu, Hsing-Wei ; Lesso, William ; Tzeng, Jang-Ruey ; Zinn, C. Dale - Orlando : International Institute of Informatics and Systemics, 2009, 46-51

ISBN
978-1-934272-57-2

Skup
The 13th World Multi-Conference on Systemics, Cybernetics and Informatics (WMSCI 2009)

Mjesto i datum
Orlando, Sjedinjene Američke Države, 10-13.07.2009

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
Project management ; computer-based approach ; decision-making model ; computer simulation ; random variable ; ANOVA ; post hoc comparisons ; confidence interval for the mean project duration

Sažetak
Project management is a discipline of outstanding importance, especially in cases when a certain task requires substantial human, technical and financial resources to be accomplished. When estimating project duration and its costs, as well as identifying its critical path activities, project managers can gain crucial support from computer simulation. The decision-making model presented in this paper is based on the assumption that activity durations can be defined as random variables that follow a triangular or beta PERT distribution. In order to estimate project duration as accurately as possible, the proposed computer-based model envisages a higher number of simulation sets. By using the analysis of variance (ANOVA) and post hoc comparisons we are able to determine simulation sets whose averages of project duration have no statistically significant differences. After their frequency distribution is formed, we can calculate the confidence interval for the mean project duration, which is one of the key pieces of information in project management.

Izvorni jezik
Engleski

Znanstvena područja
Ekonomija



POVEZANOST RADA


Ustanove
Filozofski fakultet, Osijek

Autor s matičnim brojem:
Gordana Dukić, (260082)

Časopis indeksira:


  • Scopus