朝鲜语口语与书面语实词间相关关系的一元线性回归分析

Correlation between Content Words in Spoken and Written Korean:A Univariate Linear Regression Analysis

一元线性回归分析主要研究两个变量之间的线性相关关系,是根据自变量x和因变量y的相关关系建立x与y的线性回归方程进行预测的方法。本文基于大型朝鲜语口语和书面语语料库,利用一元线性回归分析方法,计算各类实词之间的相关系数,并对其进行排序,再对中度以上的相关关系建立一元线性回归方程,并以此对朝鲜语口语和书面语进行比较研究。

Univariate linear regression is commonly employed to study the linear relationship between two variables,the independent variable x and the dependent variable y.It is an approach for prediction by way of establishing the linear regression equation of x and y according to their correlation.Based on large-scale spoken and written Korean corpora,this paper uses a univariate linear regression model to calculate the correlation coefficients between each of the four categories of content words and the other twelve categories,sorts the correlation coefficients,and then establishes a univariate linear regression model of the correlation above the moderate,which is used to compare spoken and written Korean.