A Linear Regression Model-Based Approach to Assessing Translation Efficiency in Business English Translation Teaching

As a core course of Business English majors, Business English translation plays a crucial role in the cultivation of Business English talents, and how to realize the assessment of translation efficiency in teaching has become a hot topic nowadays.This paper builds up a translation efficiency assessment index system in the teaching of business English translation around five aspects: vocabulary, syntax, context, society, and translator's factors.Random forest and Lasso regression methods were used to select 15 feature variables including sentence order and collocation between words.The multiple regression linear model was chosen to construct a model for assessing translation efficiency in business English translation teaching, and the model was estimated and tested.The least squares method was used for estimation, and all the parameters were significant (Sig<0.05)except for the variables compound sentences, sentence structure and situational intermingling.The distribution of the residuals of the model approximates to the normal distribution, which satisfies the assumption of normality and the assumption of independence, and possesses a good fit and some explanatory power.