Statistics Anxiety Research Articles

Assessing Student Preferences for Quantitative Methods Courses Using Discrete Choice Experiments

Understanding how students choose quantitative methods courses is important for both instructors and departments: Meeting student preferences increases motivation and engagement, enhances learning, can contribute to reducing statistics anxiety, and ensures enrollment. This article uses a discrete choice experiment to causally assess sociology students’ course preferences. In contrast to existing experimental interventions, choice experiments allow for an estimation of treatment effects prior to implementing an instructional design. Using data collected at a German university as a case study, this contribution provides insights and discusses practical implications of student preferences for quantitative methods courses. In the study, students prefer courses that use hands-on forms of assessment, follow a regular schedule, offer more credit points, and mix undergraduate and graduate students. The accompanying online material provides a step-by-step introduction to the design of discrete choice experiments, allowing a replication of the study and an implementation of the methodology in other contexts.

Exploring statistics anxiety and self-efficacy in psychology undergraduate students

Statistics anxiety is experienced by a large proportion of psychology students, even though conducting statistical analyses is a fundamental skill for students to acquire. The research on statistics anxiety has tended to explore either dispositional factors (e.g. personality) or situational factors (e.g. teacher effects). One potential predictor that has not yet been considered is statistical self-efficacy; the belief that one can successfully complete statistical tasks. The present study aims to clarify whether statistical self-efficacy is a predictor of any aspects of statistics anxiety in psychology students. In this study 100 undergraduate students (89% female identifying), in the second and third (final) year of a psychology degree in the UK, completed the Statistics Anxiety Rating Scale (STARS), the Statistics Self-efficacy scale (SSE), and a measure of trait anxiety. A hierarchical regression showed a significant negative relationship between statistical self-efficacy and all aspects of statistics anxiety, showing that students who are more confident in their statistical skills experience less statistics anxiety. Findings are discussed in relation to both understanding statistics anxiety and developing interventions to alleviate statistics anxiety, such as mentoring for students with diagnosed clinical anxiety conditions or interventions that aim to improve a student’s self-efficacy.

Attitudes towards statistics and statistical performance: A mediation model of statistics anxiety and academic procrastination.

Students often harbour negative attitudes towards research methods and statistics courses, and such attitudes may be associated with harmful cognitive and behavioural responses. Research on these effects has been restricted to the investigation of direct links between attitudes towards statistics, statistics anxiety, academic procrastination, and course performance. This study sought to examine the interconnected impact of attitudes towards statistics, statistics anxiety, and procrastination, on course performance in a cohesive model. It was predicted that attitudes towards statistics would indirectly affect statistical performance via statistics anxiety and procrastination in a sequential manner. The sample comprised 171 undergraduate psychology students from Australian universities. An online questionnaire collected information on participant demographics, attitudes towards statistics, statistics anxiety, procrastinatory behaviours, and performance in participants most recently completed statistics course. Data were collected cross-sectionally. All responses were anonymous. A sequential mediation analysis revealed a significant indirect effect of statistics anxiety and procrastination, controlling for age and gender. The results showed that more negative attitudes towards statistics are associated with greater statistics anxiety, which is in turn associated with greater procrastination, and finally with lower statistical performance. It was concluded that students who view their statistics courses as a threatening experience may fail to see value in their statistical education, which is associated with heightened statistics anxiety, increased avoidance of course-related activities, and in turn poorer course performance. Practical implications of the findings are also discussed.

Fear of the unknown: Relationship between statistics anxiety and attitudes toward statistics of university students in three countries

AbstractIn an increasingly data‐driven world, statistical literacy is a necessity yet statistical learning is often inhibited by statistics anxiety. Using the Auzmendi Scale to Measure Attitude toward Statistics (ASMAS), this study examines how statistics anxiety in university students is related to other dimensions of their attitudes toward statistics and how statistics anxiety and other dimensions change following introductory statistics instruction. Based on data collected from Spain, Canada, and Australia, this study finds that anxiety is negatively related to security–confidence, pleasantness, and motivation. The structure of these relationships is consistent across countries and disciplines and remains in place after statistics instruction. Further, by the end of an introductory statistics course, students report higher security–confidence and pleasantness but lower anxiety. Results thus suggest where efforts to improve students' experience with statistics might need to be directed, and the paper concludes with a discussion of the implications of these results for statistics instruction.

Enhancing learning and attitude toward statistics with a microlearning approach using an animated video

Statistics anxiety is a reality among many students that may affect their academic and professional lives. Although there are instructional strategies proven to demonstrate advanced statistical concepts, a method to mitigate statistics anxiety in introductory courses is lacking. This research examines the effectiveness of three interventions used to teach the concept of Levels of Measurement, an introductory topic in statistics: text-based lecture notes, comic strips, and microlearning using a two-minute animated video. This study was conducted over six semesters between Spring 2020 and Fall 2022 in an undergraduate introduction to educational technology course, and 571 students participated. Data collected included students’ attitudes toward statistics measured by the Attitude Toward Statistics scale, a one-word response expressing their attitudes toward statistics before and after the interventions, and pre-and-post tests examining their understanding of the concept. The microlearning groups outperformed the other groups on the post-test, and the ATS scores significantly, indicating that this intervention is more effective in improving students’ learning of the levels of measurement and attitudes toward statistics. Educators can implement microlearning using animated videos in introductory courses to reduce students’ statistics anxiety, thereby facilitating their academic progress.

Re-Validation and Exploration of Modified Versions of the Statistics Anxiety Scale Developed for College Students in the United States

Re-Validation and Exploration of Modified Versions of the Statistics Anxiety Scale Developed for College Students in the United States

Designing an introductory statistics subject for students with diverse educational backgrounds and chosen qualifications

This is a case study on the design of a first-year undergraduate statistics subject at La Trobe University, entitled Making Sense of Data, which is taken by students from various disciplines. To account for students' diverse educational backgrounds and chosen qualifications, this subject is designed such that all students complete core statistics concepts, while a third of the subject contains stream-specific content. This subject design provides students with a solid foundation in statistics, while addressing the demand for a flexible first-year statistics subject which is accessible and relevant for students enrolled in a variety of tertiary degrees. This structure allows for stream-specific lectures, computer lab material, assessments, and even statistical software programs to be used across different streams. The design also incorporates strategies for addressing statistics anxiety within the curriculum. In this paper, we present the outcomes of this subject design in terms of student performance, engagement and satisfaction. We also present iterative and reflective changes that have been made to the subject over time, in response to student and staff feedback, and discuss the impact these changes have had on student outcomes.

To behave or not (un)ethically? The meditative effect of mindfulness on statistics anxiety and academic dishonesty moderated by risk aversion

Despite the growing interest in mindfulness in higher education, the literature on its relation to decision-making under risk (i.e. academic misconduct) and statistics anxiety is scarce. The present research shall fill this gap. Based on the prospect theory, we assessed the mediating effect of mindfulness on the relationship between statistics anxiety and academic dishonesty moderated by risk aversion. Data were collected from 791 undergraduate students in six Israeli academic institutions studying for bachelor’s degrees in social sciences. Questionnaires included the following measures: risk behaviour according to the prospect theory framework, Mindful Attention Awareness Scale, Statistics Anxiety Rating Scale, Academic Misconduct Scale and sociodemographic variables. Correlations among these variables were explored. The data was analysed using Structural Equation Modelling (SEM). The results indicate that the variance in academic dishonesty is explained by students' statistics anxiety with a mediation of Mindfulness moderated by Risk Aversion. Mindfulness negatively affects Academic Dishonesty, while Risk Aversion has a significant positive effect on Mindfulness. Finally, among individuals with high statistics anxiety, Risk Averse individuals show significantly higher Mindfulness than Risk Seekers. We conclude that mindfulness-based interventions might be a constructive tool to reduce risk-taking and promote ethical decision-making among individuals who experience high levels of statistics anxiety. Furthermore, developing mindful skills may help individuals with higher anxiety levels neutralize these unwanted feelings and get along with their learning tasks. Hence, avoid academic unethical behaviours.

Analysis of the Indonesian Version of the Statistical Anxiety Scale (SAS) Instrument with a Psychometric Approach

This study aims to validate the psychometric approach (using the RASCH Model and Confirmatory Factor Analysis) on the Indonesian version of the Statistical Anxiety Scale (SAS) instrument. Sampling in this study used cluster random sampling with a total sample of 1651 which was divided into 3 regions of Indonesia (Western Indonesia, Central Indonesia and Eastern Indonesia) with details of 457 males (27.46%) and 1194 females (72.54%). The number of samples from the West Indonesia region was 922 people (55.71%), the Central Indonesia region was 605 people (36.76%), and the Eastern Indonesia region was 124 people (7.53%). The results of the factor analysis (CFA) show that the dimensions/elements of the SAS instrument meet the criteria which are then continued using the Rating Scale Model (RSM) approach. From the results of the tests performed, it shows that all items on the Statistical Anxiety Scale (SAS) instrument meet the specified criteria. Thus, the SAS instrument adopted in the Indonesian context can be used to measure students' statistical anxiety. The results of the research conducted became the initial capital to increase students' statistical anxiety considering that statistics courses are needed in completing studies, especially quantitative research.

Cerrahi Hastalıkları Hemşireliğinde Lisansüstü Eğitime Devam Eden Hemşirelerin İstatistik Kaygı Düzeylerinin Değerlendirilmesi

Giriş: Cerrahi hastalıkları hemşireliği (CHH) alanında lisansüstü eğitimine devam eden/tamamlayan hemşirelerin, kanıta dayalı uygulamaların geliştirilmesi için bilimsel araştırmalara katılmaları, takip etmeleri ve araştırma bulgularını/sonuçlarını yorumlayabilmeleri gerekmektedir. Ancak istatistik kaygısı, hem bilgi-beceri kazanmayı hem de bilimsel araştırmalara katılmayı olumsuz etkileyen bir faktördür. Amaç: CHH alanında lisansüstü eğitime devam eden hemşirelerin istatistik kaygı düzeylerinin değerlendirilmesidir. Gereç ve Yöntemler: Tanımlayıcı tipte olan bu araştırma Türkiye’deki üniversitelerde cerrahi hastalıkları hemşireliği alanında lisansüstü eğitime devam eden ve araştırmaya katılmaya gönüllü olan 114 hemşirenin katılımıyla gerçekleştirildi. Veri toplamada Hemşire Tanıtıcı Bilgi Formu ve Lisansüstü Eğitim Öğrencilerine Yönelik İstatistik Kaygısı Ölçeği (LEÖYİKÖ) kullanıldı. Bulgular: Hemşirelerin LEÖYİKÖ toplam puan ortalamaları 32.3±9.6 bulundu. Hemşirelerin ölçek toplam puan ortalamalarının cinsiyete, lisansüstü eğitim dönemine ve araştırma yöntemleriyle ilgili kursa katılma durumlarına göre istatistiksel olarak anlamlı farklılık gösterdiği belirlendi. Yedi değişken için, gruplar arasında kaçınma alt boyut puan ortalamaları açısından istatistiksel olarak anlamlı farklılık bulundu. Sonuç ve Öneriler: Hemşirelerin istatistik kaygılarının ortalamanın altında olduğu görülmektedir. Erkek, yüksek lisans eğitime devam eden ve araştırma yöntemleriyle ilgili kursa katılmayan hemşirelerin istatistik kaygıları daha yüksektir. Erkek hemşireler, akademisyen olmayanlar, yüksek lisans eğitimine devam edenler, bilimsel yayın takip etmeyenler, bilimsel araştırma ve toplantıya katılmayanlar ile araştırma ve istatistik yöntemlerine ilişkin kursa katılmayan hemşireler istatistikten kaçınma eğilimi göstermektedirler. Nispeten kaygı düzeyleri yüksek seyreden erkek, yüksek lisans eğitimine devam eden ve araştırma yöntemleriyle ilgili kurslara katılmamış olan hemşirelerin istatistik kaygısı ile olumlu baş edebilmeleri ve kaçınma eğilimlerinin azaltılabilmesi için desteklenmeleri önerilmektedir.

Let us get numerical: explaining Political Science student preferences for quantitative studies

The global push to reorient social sciences in an increasingly technical direction might have a clear labour-market justification, but the efforts face headwinds from both faculty and students. This research is concerned with the fear that students would resist such a reorientation. Much of the pedagogic social-science research seeks ways to alleviate student math and statistics anxiety, an obstacle that would apply regardless of whether students receive such instruction in their field or indirectly through required cognate courses. The literature tends to emphasise instructor perspectives, but we focus on student attitudes. Using a survey of Political Science students at 11 institutions in the Western Balkans we predict student preferences for empirical, statistical, mathematical and computational instruction. Our explanatory variables fall into three batches: computer literacy, educational expectations and perception of career usefulness. Our main conclusion is that students expecting (1) to acquire practical training or (2) to develop research skills are especially likely to embrace a curriculum oriented toward empirical/statistical/mathematical/computational applications in Political Science, an association that grows stronger as the students remain enrolled. Insofar as a programme or institution can recruit for, or cultivate, such expectations, they can expect students relatively receptive to the technical direction in Political Science education.

Voluntary E-Learning Exercises Support Students in Mastering Statistics

University students often learn statistics in large classes, and in such learning environments, students face an exceptionally high risk of failure. One reason for this is students’ frequent statistics anxiety. This study shows how students can be supported using e-learning exercises with automated knowledge of correct response feedback, supplementing a face-to-face lecture. To this end, we surveyed 67 undergraduate social science students at a German university and observed their weekly e-learning exercises. We aggregated students’ exercise behavior throughout the semester to explain their exam performance. To control for participation bias, we included essential predictors of educational success, such as prior achievement, motivation, personality traits, time preferences, and goals. We applied a double selection procedure based on the machine learning method Elastic Net to include an optimal but sparse set of control variables. The e-learning exercises indirectly promoted the self-regulated learning techniques of retrieval practice and spacing and provided corrective feedback. Working on the e-learning exercises increased students’ performance on the final exam, even after controlling for the rich set of control variables. Two-thirds of students used our designed e-learning exercises; however, only a fraction of students spaced out the exercises, although students who completed the exercises during the semester and were not cramming at the end benefited additionally. Finally, we discuss how the results of our study inform the literature on retrieval practice, spacing, feedback, and e-learning in higher education.

The Psychometric Properties of the Statistical Anxiety Scale were Examined using Confirmatory Factor Analysis (CFA) and Neural Network Analysis among Students of Taif University

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.

Age Guessing: A Game to Introduce Fundamental Statistical Concepts

We develop a spreadsheet-based game to illustrate fundamental statistical concepts in the first class of an undergraduate Statistics course to motivate students about the topics that they will learn in upcoming classes. This game has been implemented by Google Forms and Google Sheets and can be played in both online and in-person classes of small and large sizes. Statistics is one of the most anxiety-inducing courses for undergraduate students, especially if mathematics is not the focus of their program. Negative anecdotes about the course, mathematics anxiety, and not knowing what the course is exactly about and how practical it can be are among the reasons that contribute to statistics anxiety. The first class provides a good opportunity for an instructor to mitigate these negative impressions and to set a positive attitude toward the course. A pre- and post-game group discussion that we have conducted systematically for six years suggests that the game addresses the students’ negative impression about the course and helps them gain a clearer understanding of the tools and skills they will learn in Statistics. Supplementary materials for this article are available online.

Statistics anxiety or statistics fear? A reinforcement sensitivity theory perspective on psychology students’ statistics anxiety, attitudes, and self-efficacy

This research investigates the role of reinforcement sensitivity theory (RST) in statistics education among two distinct samples of undergraduate psychology students. In Study 1, 318 students in a third-year statistics course completed self-report measures of RST, anxiety, attitudes, and self-efficacy concerning the study of statistics. In Study 2, 577 students from first-, second-, and third-year statistics courses participated. Controlling for age and gender, both studies found students who were high in goal-drive persistence reported lower statistics anxiety, higher statistics self-efficacy and more favourable attitudes toward learning statistics, while students who were high in the tendency to avoid threat reported higher statistics anxiety. Those with a more sensitive behavioural inhibition system reported greater statistics anxiety and less favourable attitudes, in Study 2 but not Study 1. Results indicate that RST dimensions account for as much as 23% of additional variance in statistics anxiety, 18% in statistics self-efficacy, and 11% in attitudes, after controlling for age and gender. These studies highlight the utility of RST dimensions, notably goal-drive persistence, threat sensitivity, and behavioural inhibition, in providing critical information as to personality differences among students that need to be considered when developing programs targeting statistics anxiety, attitudes, and self-efficacy.

Statistics support and anxiety explored

Abstract Most higher education institutions in the UK now offer some form of additional individual support for mathematics and statistics. Whilst numerous studies have shown mathematics support can improve grades and reduce failure rates, there is a lack of research on other outcomes of interest such as anxiety or confidence, and very little research relating specifically to statistics support. This study uses quantitative and qualitative results from student questionnaires to evaluate the effectiveness of support in reducing anxiety and increasing confidence immediately after the first statistics support session and in the longer term. Comparisons of and preferences for online or face-to-face sessions and other aspects relating to anxiety were also explored. Key quantitative findings include a significant reduction in statistics anxiety after only one session of statistics support and a long-term increase in confidence with statistics. When asked how support impacts on anxiety or confidence, key themes emerging included feeling comfortable asking questions in statistics support, tailoring to individual needs and confirmation of understanding. The majority of students preferred face-to-face sessions over online particularly those with higher levels of statistics anxiety. Although differences were generally not significant, higher levels of anxiety were observed before online sessions and greater changes in anxiety occurred during face-to-face sessions.

Grasping the STARS: A comprehensive study on statistics—Anxiety levels among engineering students

Engineering students often face the challenge of comprehending and applying statistical concepts to evaluate and assess research. This research seeks to investigate the factor structure of Statistics Anxiety Rating Scale (STARs), which comprises six domains with 51 items. The questionnaire was administered to engineering students currently enrolled in a statistics class, and the data were analyzed using Statistical Package for the Social Sciences. The study sheds light on the factors that contribute to students’ statistics anxiety when taking a statistics course. The findings highlight the elements that influence statistics anxiety, educators and institutions can develop targeted interventions and support mechanisms to enhance students’ statistical competence and overall learning experience. This research not only addresses the unique challenges faced by engineering students but also holds implications for fostering statistical literacy across various disciplines.

THỰC TRẠNG LO ÂU THỐNG KÊ Ở SINH VIÊN

The present study was conducted to investigate statistics anxiety, the relation between attitude towards statistics, exposure to statistics, and signs of statistics anxiety among undergraduate students. A survey and quantitative analysis were conducted, which were proven acceptable and reliable. The results of the study in a sample of students majoring in social sciences and humanities, education sciences, and other majors (N = 186; MAge = 19.66; 86% female) did not show a difference in signs of students’ experience with statistics. The results also indicated negative attitude towards statistics is correlated with a display of statistics anxiety signs among students. Variance analyses showed that there is no statistically significant difference in terms of exposure to statistics, attitude towards statistics, and statistics anxiety among student groups with different demographic characteristics. Implications for future studies on statistics anxiety will also be addressed

Toward a Better Understanding of Statistical Significance and p Values in Nursing

Background: Nursing aims to rely on the best evidence, yet nurses frequently struggle with statistics, impeding the integration of research into practice. The misuse of statistical significance and p values is a pervasive issue, widely debated across disciplines but often overlooked in nursing.Objective: This study seeks to elucidate key arguments surrounding the misuse of p values, assess their relevance to nursing, and propose recommendations for improvement.Approach: Conducting a critical literature review on the interpretation and reporting of statistical significance and its practical implications among nurses, nursing students, and scholars.Results: The literature reveals widespread misunderstandings of probability concepts in classical statistics, leading to the misuse of p values. Some scholars propose abandoning p values altogether due to these challenges. Rather than dismissing p values, this article provides insights into their historical context and proper application. Recommendations are offered for accurately interpreting results and integrating supplementary metrics. Fostering statistical competencies already at the undergraduate level can enhance statistical literacy and alleviate statistics anxiety among nursing students, a prevalent issue. Early exposure to statistical methods in nursing education empowers nurses to actively engage in research. Additional recommendations include preregistering analysis plans to mitigate publication bias and exploring alternative approaches such as Bayesian methods.Conclusions: While p values serve as a valuable tool for preliminary assessment against randomness in nursing research, their widespread misunderstanding necessitates multiple measures for accurate interpretation and understanding of statistical significance. It is imperative for nurse educators and researchers to incorporate these recommendations into their practices.

Prevalence and predictors of statistics anxiety among sociology and social work students

Anxiety in the context of quantitative reasoning courses is a complex and highly prevalent problem, particularly among students majoring in the arts, humanities, and social sciences. Gaining an accurate understanding of the anxiety levels experienced by students enrolling in statistics courses can be regarded as one of the most important factors affecting students’ learning and achievement in these courses. In the current study, the Statistical Anxiety Rating Scale was applied to explore the prevalence and predictors of statistics anxiety among sociology and social work undergraduate students at Sultan Qaboos University (n=142). The results show that almost 71% of the examined students had experienced some aspects of statistics anxiety, with sociology students scoring noticeably higher than social work students. The leading predictors of higher statistics anxiety levels found in this study were as follows: test and class anxiety (80.2%) and interpretation anxiety (79.1%). Moreover, Welch’s test results show significant gender differences, with female students reporting higher levels of anxiety across all subscales than their male counterparts. Finally, some practical strategies of reducing statistics anxiety are discussed.
 Keywords: Statistics anxiety, gender differences, sociology, social work, Oman