Evaluation of the Factors Affecting the Career Choice of Statistics Students With Fuzzy Dematel and Fuzzy Topsis Methods

Career choice is a pivotal decision that shapes an individual's professional path and has a profound impact on their life. Various factors influence this process, and identifying and prioritizing these influences in real-world scenarios is often challenging. Ranking the factors that are effective in career choice is a problem that can be handled with Multi-Criteria Decision Making (MCDM) methods. Fuzzy logic approach can be used together with MCDM methods. The concept of Fuzzy Logic was developed by Zadeh (Zadeh, 1965) and fuzzy versions of many MCDM methods have been proposed in this context. This study investigates which fields of study hold greater significance during the career planning and preference stages for statistics department graduates, taking into account the influences they encounter in their career selection process. The relationships between the main criteria were analyzed using the Fuzzy DEMATEL method, based on input from expert decision-makers. Subsequently, an initial table was created using the Fuzzy TOPSIS method, incorporating criteria weights derived from the Fuzzy DEMATEL analysis. This approach enabled the identification of the most appropriate decision alternatives and rankings across five different fields of study. The findings indicate that individuals who choose the statistics department due to factors such as numerical ability, skills, interests, environmental influences and family structure, professional values, psychological needs, earnings potential, ease of job acquisition, coursework, and social opportunities tend to prefer working as data specialists after graduation.