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The research aims to determine the factors affecting PISA 2018 reading skills using Random Forest and MARS methods and to compare their prediction abilities. This study used the information from 5713 students, 2838 (49.7%) male and 2875 (50.3%) female in the PISA 2018 Turkey. The analysis shows the MARS method performed better than the Random Forest method. The most significant factor affecting reading skills in Turkey is “the number of books in the house” in both methods. The variables the MARS method finds significant are “students' perception of difficulty, motivation for reading skills, father’s educational status, reading pleasure, bullying experience of the student, mother's educational status, attitude towards school, classical artifacts at home, supplementary school books at home, competition at school, competitive power, cooperation perception at school, reading frequency, self-efficacy, poetry books at home, anxiety about reading skills and teacher support.” However, the other variables had no relation to prediction. This study is expected to serve as an example of data mining application in educational research

This study tries to compare similarities and differences in Organisation for Economic Cooperation and Development (OECD) countries in terms of traffic accidents utilizing Multidimensional Scale Analysis (MDS), and one of Multivariate Statistical Analysis Techniques. In the study, MDS analysis was carried out utilizing basic indicators such as the number of injuries, deaths and the number of accidents resulting in material damage in the traffic accidents that happened in 2017. As a result of the analysis, stress values and R 2 (correlation coefficient) values turned out to be 0.0000 and 1.0000, respectively. That the stress value has resulted as zero shows that there is no inconsistency, and the fact that R 2 value has been found to be 1 indicates that the accuracy rate of this analysis is high and the values are in excellent coherence. According to results obtained from the analysis, it is seen that Malta and Liechtenstein, in particular, have appeared to be in a very different position from other countries when the countries are compared in terms of traffic accidents. When the matrix of the differences is examined; Turkey and Liechtenstein have seemed to be the two countries very different from each other. It is clear that traffic accidents, a global public health problem, have great impacts on individuals, societies and national economies. Particularly, it will be possible to decrease human and economic losses to minimum levels when the countries with similar traffic accident indicators come together, develop national and international projects and apply them.

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The aim of this study was to investigate the factors affecting the science success of eighth-grade students using the Ordinal Logistic Regression method. In this study, information collected from a total of 4224 students, 2202 (52.1%) male and 2022 (47.9%) female, who participated in the ABIDE 2016 application was used. The scores obtained from the science course of the students entering the ABIDE 2016 application were transformed into categorical ones according to the determined threshold values. In the analysis, the categorical science success score was used as the predicted variable, and 15 variables that were thought to affect science success were used as predictive variables. The data obtained later were examined by the Ordinal Logistic Regression method. As a result of the examination, the factors affecting science success were determined as peer bullying, perceived self-efficiency, value given to the course, parental attention, family pressure, father’s educational status, mother's educational status, monthly income, having a computer or tablet, having a room of one's own, student's educational goal and participation in science support courses. The findings were found to be remarkably similar to those found in the literature. This indicates that the OLR method is quite effective in predicting training data. Such research is expected to be handled objectively and without bias.