高校课程考试成绩的非均衡多因素方差分析  

Multi-Factor ANOVA of Unbalanced Data on College Course Test Scores

作　　者：刘笑涵 乔舰[1] 

机构地区：[1]中国矿业大学理学院,北京

出　　处：《统计学与应用》2024年第6期2586-2599,共14页Statistical and Application

基　　金：本文受中国矿业大学(北京)校级课程建设与教改项目(编号:J230704)支持。

摘　　要：本文基于非均衡数据多因素方差分析理论对高校某公共基础课程考试成绩进行了统计分析。文中先对相关方差分析理论基础进行了综述,然后基于R软件对某课程考试的真实数据集进行了详细的方差分析研究,给出了丰富的图表展示,结果表明本文所设定的两个自变量的交互影响不显著,但学院类别和学生性别对平均成绩影响显著。基于此分析结果,本文给出了一些教学指导建议。 This paper makes a statistical analysis on college course test scores based on the theory of Multi-factor ANOVA of unbalanced data. Firstly, the theoretical basis of relevant ANOVA is summarized, then based on R software, the detailed ANOVA process for a real data sets of a course exam is conducted, a rich chart shows is given, the result shows that the interaction influence of the two independent variables is not significant, but the college category and student gender have a significant influence on the average score. Based on the analysis results, this paper gives some teaching guidance suggestions.

关 键 词：非均衡数据多因素方差分析 课程考试成绩 离差平方和 

分 类 号：G63[文化科学—教育学]