Determination of The Factors Affecting The Success of The Students of Econometry Department: Manisa Celal Bayar University Sample

To increase the success level of university students and to be trained as qualified individuals are the driving force of the country's economy and social development. In the literature, many academic studies towards this aim were done by factor analysis method; but it seems that no study has been done for determining the factors that affect the success of students studying in the Department of Econometrics. In this study, to 210 students studying in the Department of Econometrics at Manisa Celal Bayar University Faculty of Economics and Administrative Sciences in 2015-2016 education period a questionnaire consisting of 54 questions was applied. As a result of factor analysis 8 factors were found that affect students' achievements. These factors explain 65% of the variance

Grouping of the companies in different scales by fuzzy cluster analysis operating in the Aegean region of KOSGEB (SMEs)

In recent academic researches and applications, fuzzy clustering theory is used to classify concepts which state uncertainty. In clustering studies, if there is an uncertainty in determining clusters or cluster memberships of some objects, it would be better to use fuzzy clustering approach. Furthermore, Fuzzy Clustering Analysis differ from other statistical analysis as flexible structure, more practical and not based on any assumption. As a result of that, modelling and even copying of many systems with the help of fuzzy systems have been caused considerable development in our lives as well as in scientific field. In this study, considering the all advantages of fuzzy clustering analysis, the companies operating in the Aegean region of KOSGEB with different scales are classified. The data obtained according to the criteria determined by KOSGEB are used. Classification is made by three different scales using fuzzy clustering methods. Fuzzy inference system has been created to provide convenience for applications of fuzzy modelling structure and fuzzy clustering algorithms. For classification analysis in this study were obtained a more flexible model. Also it is intended to provide opportunity of quick analysis and evaluation to researchers and practitioners through a software created using MATLAB.</span