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Self-proficiency, distinct from self-efficacy, is a more comprehensive dimension in assessing students’ abilities. Moreover, the TAI cooperative learning model is believed to be relevant in enhancing self-proficiency, as well as other mathematical ability dimensions, particularly in Statistics course. Therefore, this study aimed to assess the enhancement of self-proficiency, mathematical problem-solving and mathematical communication by implementing the TAI (Team-Assisted Individualization) Cooperative Learning Model in the context of Non-Parametric Statistics, which is a core undergraduate statistics course. A quasi-experimental approach with purposive sampling, which comprised 72 observation samples divided into control and experimental groups, was used to conduct this study. Evaluation instruments consisted of mathematical problem-solving test, mathematical communication test, and self-proficiency test, along with observation sheets. Furthermore, these statistical analysis tools were used included the Paired Sample t-test, the Independent Sample t-test, as well as the ANCOVA (Analysis of Covariance). The results, obtained through various assessments that examined mean differences and comprehensive statistical analyses, comprised both independent and dependent sample evaluations. The evaluations consistently showed substantial increase in problem-solving ability, communication skills, and self-proficiency in the cohort subjected to the experimental conditions, surpassing those observed in the control group. The ANCOVA estimations further validated the meaningful effect of the teaching strategy on the enhancement of the tested aspects. In conclusion, this study implied that the implementation of TAI learning model effectively enhanced all three objectively and measurably assessed aspects, particularly in the context of non-parametric statistics course.

The inconsistent distribution of dividends is a unique phenomenon and it needs to be examined. Therefore, the purpose of this study is to examine ten predictors affecting dividend policy of the inconsistent distribution of dividends. This study used the purposive sampling method to analyze the data that were obtained from a total sample of 133 observation objects collected in the 19 real estates, property, and building construction companies listed on the IDX Between 2013 - 2019. Furthermore, the method used is hypotheses testing and statistical analysis tool used is the hierarchical multiple panel data regression with the Least Squares Dummy Variables. The results obtained from panel A are firm risk, financial leverage, and investment opportunity that affect the dividend policy. Meanwhile, the panel B results are company risk, financial leverage, investment opportunity, and previous dividend, although the previous dividend had no effect due to the different direction of influence. This study proves the determinants and relevance of the parametric statistical analysis in the inconsistent distribution of dividends. Moreover, it is useful for managerial practitioners to pay attention to predictors for increasing company performances and to ensure investors obtain optimal return of their dividend.

The purpose of this study is to analyze the increase in the mathematical problem-solving (MPS), mathematical communication (MC), and self-proficiency (SPr) abilities of students by applying the team-assisted individualization type (TAI) of the cooperative and conventional learning models for the experimental and control classes. This is a quasi-experimental study comprising a sample of 50 and 42 students studying for an undergraduate degree in statistics for the experimental and control classes, respectively. Students’ mathematical prior knowledge (MPK) is grouped into three levels, namely high, medium, and low. The instruments used are the MPS test, the MC test, the self-proficiency scale, and observation sheets. Statistical analysis instruments used are parametric and non-parametric statistics, such as prerequisite tests for normality and homogeneity of variance, mean difference tests in two or more groups, the post hoc test, and description and interaction tests. The results showed an increase in MPS, MC, and SPr in the experimental class, which is higher than in the control class. Furthermore, there is no interaction between the experimental and control classes despite a significant correlation between MPS, MC, and MPS. These findings are relevant to mathematics and statistics teaching because it has been proven to improve students’ MPS, MC, and SPr; hence, learning outputs can be achieved objectively, specifically for operations research teaching.