A Confirmatory Factor Analysis of the Structure of Statistics Anxiety Measure: An Examination of Four Alternative Models

By Vahedi, Shahram; Farrokhi, Farahman et al. | Iranian Journal of Psychiatry, Summer 2011 | Go to article overview

A Confirmatory Factor Analysis of the Structure of Statistics Anxiety Measure: An Examination of Four Alternative Models


Vahedi, Shahram, Farrokhi, Farahman, Bevrani, Hossein, Iranian Journal of Psychiatry


Objective: The aim of this study is to explore the confirmatory factor analysis results of the Persian adaptation of Statistics Anxiety Measure (SAM), proposed by Earp.

Method: The validity and reliability assessments of the scale were performed on 298 college students chosen randomly from Tabriz University in Iran. Confirmatory factor analysis (CFA) was carried out to determine the factor structures of the Persian adaptation of SAM.

Results: As expected, the second order model provided a better fit to the data than the three alternative models. Conclusions: Hence, SAM provides an equally valid measure for use among college students. The study both expands and adds support to the existing body of math anxiety literature.

Keywords: Anxiety, Psychometrics, Questionnaire, Statistical factor analysis

Iran J Psychiatry 2011; 6:92-98

For many years, psychologists have been interested in finding variables that can predict academic performance (AP). In recent years, research on the relationships between personality and AP has not only analyzed the general relationships between the two variables but has also focused on the relationships between anxiety and performance in specific academic domains. As a result, several authors have investigated the predictive power of personality on performance in statistics courses.

It has been estimated that as many as 80% of graduate students experience uncomfortable levels of statistics anxiety, and statistics examinations are more anxiety-inducing than other types of examinations (1).

Statistics anxiety may even hinder a student from completing a degree or deter a talented student from thinking about a career as a professor (2). Identifying individuals suffering from statistics anxiety and gaining a better understanding of the domains that contribute to such anxiety is a start to addressing the problem of statistical illiteracy today. Statistics anxiety has been defined as anxiety that occurs because of encountering statistics in any form and at any level, involving a complex array of emotional reactions (apprehension, fear, nervousness, panic, and worry) that hinder the learning process (3). oreover, statistics anxiety is situation-specific, inasmuch as the symptoms only emerge at a particular time and in a particular situation-specifically, when learning or applying statistics in a formal setting (4 and 2).

Research indicates that statistics anxiety is a multidimensional construct (5, 6 and 2). Using factor analysis, Earp (7) identified five components of statistics anxiety, namely: (a) anxiety, (b) performance, (c) attitude towards class, (d) attitude towards math, and (e) fearful behavior.

A growing body of research has documented a consistent negative relationship between statistics anxiety and course performance (8). In fact, statistics anxiety has been found to be the best predictor of achievement in research methods courses (9) and statistics courses (10). Moreover, a causal link between statistics anxiety and course achievement has been established. In particular, Onwuegbuzie and Seaman (11) found that graduate students with high levels of statistics test anxiety who were randomly assigned to a statistics examination which was administered under timed conditions tended to have lower levels of performance than did their low anxious counterparts who took the same test under untimed conditions.

Earp (7) established an instrument named 'SAM' to measure Statistics Anxiety in a community college. 'SAM' had high internal consistency reliability (Cronbach's coefficient alpha = 0.82-0.95) and construct validity. SAM needs to be more adequately validated because counselors have used it extensively. Based on exploratory factor analysis (EFA) in Earp (7), in this study, we tested four models. Our research questions were as follows:

Do statistics anxiety items generated to reflect the five identified domains (Anxiety, Performance, Attitude Towards Class, Attitude Towards Math, and Fearful Behavior factor) fit appropriately into the five domains?

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