Identifying interesting relationships between pairs of variables in large data sets is increasingly important. Here, we present a measure of dependence for two-variable relationships: the maximal information coefficient (MIC). MIC captures a wide range of associations both functional and not, and for functional relationships provides a score that roughly equals the coefficient of determination (R2) of the data relative to the regression function. MIC belongs to a larger class of maximal information-based nonparametric exploration (MINE) statistics for identifying and classifying relationships. We apply MIC and MINE to data sets in global health, gene expression, major-league baseball, and the human gut microbiota and identify known and novel relationships.

Detecting Novel Associations in Large Data Sets

To motivate learners to engage in writing courses and help to improve their writing performance, a mobile-game-based collaborative prewriting approach was proposed in this study. A quasi-experiment was implemented by recruiting two classes of non-English major students from a university in northeastern China. Class 1 learned to write under the guidance of the mobile-game-based collaborative prewriting method, while Class 2 in the conventional teacher-centered approach. Their writing performance was measured to evaluate the effectiveness of the proposed approach. By analyzing the scores of students’ writings in pre-test and post-test and the content of student discussions in prewriting activities, it was found that, the students in Class 1 who focused on content talk in group discussions improved more in organization of content, originality, fluency, and elaboration than those in Class 2 in post test. In addition, the findings showed that the incidence of different types of idea units in collaborative prewriting discussions had significant correlation with the ratings of different dimensions, respectively, in individual writings. Furthermore, the majority of volunteer students who finished the questionnaire endorsed the mobile-game-based collaborative prewriting approach. 

https://link.springer.com/content/pdf/10.1007/s40299-022-00645-6.pdf

Yue Tianyi

Papers

Payment-Guard: Detecting fraudulent in-app purchases in iOS system