The Psychometric Properties of the Statistical Anxiety Scale were Examined using Confirmatory Factor Analysis (CFA) and Neural Network Analysis among Students of Taif University
Mariam Hejab Alshaibani · Journal of Umm Al-Qura University for Educational and Psychological Sciences · 2024
The current study aimed to confirm the psychometric analysis of the Statistics Anxiety Scale (SAS) using Confirmatory Factor Analysis (CFA) and Neural Network Analysis among students at Taif University. The study sample consisted of 455 students from Taif University. The researcher utilized the Vigil-Colet Statistics Anxiety Scale (2008), comprising 24 items distributed across three dimensions: Test Anxiety, Table and Graph Anxiety, and Interpretation Anxiety The data were analyzed using Confirmatory Factor Analysis (CFA) and Neural Network Analysis. The study results yielded a suitable fit for the three-dimensional model of statistical anxiety with the sample data (RMSEA=0.077, CFI=0.91, TLI=0.90). The Neural Network Analysis produced indicators of centrality, proximity, and strength to highlight the importance of vocabulary in shaping the structure of the statistical anxiety concept, especially regarding the statistical anxiety dimension. Additionally, the study found moderate aspects of statistical anxiety among university students. The results were discussed in the context of previous studies related to the concept of statistical anxiety.