大数据背景下数理统计课程的教学改革与实践

Teaching Reform and Practice of Mathematical Statistics Course under the Background of Big Data

无论是传统的统计学还是大数据背景下的数据分析,都是为了使我们的工作变得更为有效,让决策更为理性而准确。海量的数据需要更高效的数据处理技术和数据处理模式。为了顺应大数据时代的发展趋势,从教育的角度来看,需要培育出具有数据处理、数据分析、数据挖掘等能力的数据分析师。本文针对西南林业大学大数据与智能工程学院的部分老师和学生做了问卷调查,分析了学院老师和学生对统计类课程教学方法和教学实践上的意见和建议,对大数据时代下统计学教学模式进行了探讨,结果表明:在教学中应主要教会学生如何把实际问题归结为恰当的统计问题,同时应培养学生对数据实时分析能力。

Both traditional mathematical statistics and current data analysis in the context of big data contribute to the improvement of effectiveness of our work,and to more accurate and rational decisions.However,massive data calls for high-efficiency technology and architecture in performing data analysis.From an educational perspective,to better adapt to the moving trend in a big data era,we should cultivate data analysts skillful in both data processing,data analysis and data mining.This article is grounded on a questionnaire survey on part of the instructors and students in the Department of Big Data and Intelligent Engineering in Southwest Forestry University.We analyzed their opinions and advice on the teaching methods and practices in statistics courses and researched the teaching modes under the big data context.The result demonstrates that instructors should focus mainly on teaching students how to translate real-world problems into appropriate statistical equivalents,and develop in them the ability to analyze data on a real-time basis.