The research investigates students’ behavior in a statistics course in their last semester of gradation, where they are produced with statistic anxiety. Its objective is to explore and find out the effect of this anxiety on the success of academic capacity and the mental wellness of a person. Also, taking into account the relation between statistics anxiety and various academic and psychological variables. Independent variables include initial enrollment, statistics anxiety, intolerance to uncertainty, and worry. Dependent variables comprise academic outcomes, kids’ attitudes toward statistics, cognitive issues concerning one’s statistical capabilities, and a tendency to procrastinate. The researcher employed sampling with questionnaires, psychological assessments, and statistical analysis techniques. These allowed to get multifaceted insight into the statistics anxiety among graduate students.
Purpose
The research problem is formulated: “How the triad, anxiety, IU (intolerance for uncertainty), and statistics anxiety, are affected by each other.” Hypotheses make clear the expected relationships, including but not limited to intolerance, which is the inability to manage uncertainty to worry, which is linked to statistics anxiety among statistics students. The effect of such variables and any changes from pretests to post-tests are evaluated.
Hypotheses
The study has a bias-free data collection research hypothesis to outline the expected relationships among intolerance of uncertainty, worry, and statistics anxiety. As it aligns with the study’s primary aim, it concentrates on this matter, which involves statistics, anxiety, and cognitive processes. Phrases such as “intolerance of uncertainty,” “worry,” and “statistics anxiety,” which are hinted at above, are explicitly given for readers to understand better.
Methodology
Participants
The article offers a research design using a methodological approach. The author made use of a quantitative approach and used a cross-sectional design. Researchers voluntarily enrolled individuals from a specified institution from a massive public university and gathered data from three varieties of graduate-level statistical introductions within two semesters.
Instruments
The study paper indicates the tools used for collecting data. Intolerance of Uncertainty Scale-12 (IUS-12): Uncertainty Tolerance, a 12-item scale, measures one’s tolerance level for not knowing. Statements on a 5-point Likert scale measure respondents’ answers. It has factor analysis and high internal consistency (Cronbach’s alpha of 0.85 at the pretest and 0.86 at the posttest). Penn State Worry Questionnaire (PSWQ): This questionnaire evaluates 16 essential items in understanding worry tendencies, one of which is reverse-scored. It has high internal consistency (Cronbach’s alpha of 0.91 at pre- and 0.88 at post-tests). Statistics Anxiety Rating Scale (STARS): The scale assesses the whole range of statistics anxiety through six factors comprising 51 items (Williams, 2013). Respondents score the following statements on a 5-point scale (from strongly agree to disagree strongly). These scales were established using factor analysis and showed high internal consistency reliability for each (ranging from Cronbach’s alpha 0.77 at the pretest to 0.93 at the posttest).
Procedure
This study was designed to invite statistics majors from statistics classes for graduates to join. Pretest and post-test questionnaires, including the IUS-12, PSWQ, and STARS instruments, were used to determine self-esteem changes before and after instruction. Confidentiality was guaranteed,d, and anonymity of the collected data was ensured.
Results
The study identified notable relationships between higher IU, worry, and statistical anxiety, which aligned with the hypotheses. The p-value using the Bonferroni method was controlled for the FWER (Family Wise Error Rate), which ensured the results were dependable. The ANOVA for repeated measures revealed a significant P-value for the dependent variables, proving the viability of the hypothesis (Williams, 2013). The research did not register any decrease in intolerance of uncertainty and worry, so it might be the case that the intervention offers only partial results. Conducting a pilot study might help to assess the validity, which means getting extra points of view on the effectiveness of the intervention and factors contributing to the outcomes. The research findings present an insight into the interaction between cognitive factors and statistics anxiety. It gives the basis for further research and possible approaches that may be used in statistics anxiety implications alleviation among graduate students.
Discussion
The article specified that graduate students from a college of education were the study participants. Data were collected through the self-representative questionnaires. Sample recruitment was dated, and students from three sections of the first STAT classes were invited. Descriptive statistics for data were used, and extra reliable statistical analysis was performed, including Pearson’s correlation coefficients and repeated measures ANOVA.
Conclusion
Considering all of the observations, the article is poorly researched. More robust sampling and study design methods would deliver results with higher validity to this research article. Suggestions include random sampling, monitoring of people over time, and using the qualitative technique. Although significant, this study cannot carry over further research because of the limitations of the study’s generalizability and the depth of understanding regarding statistics anxiety among graduate students.
Reference
Williams, A. S. (2013). Worry, intolerance of uncertainty, and statistics anxiety. Statistics education research journal, 12(1), 48-59.
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