中文课程简介

本课程将全面地介绍目前可以用于气候变化模拟和分析的最新预测分析技术和统计方法。具体覆盖的内容包括：统计学习方法概述、线性模型、时间序列分析、再抽样方法、主成分分析、决策树、聚类树、以及基于R语言的实际应用。参与本课程的学生还将参加一个小组项目，小组项目的案例研究将聚焦于山东省青岛市的气温上升。该课程将有效地帮助学生学习如何利用实际观测数据来进行气候变化建模和分析。

英文课程简介

This course provides an introduction of the up-to-date predictive analytics and statistical methods for climate change modeling and analysis. It covers topics such as basics of statistical learning, linear models, time series models, resampling methods, principal components analysis, decision trees, and cluster analysis, with practical applications in R. In the final project, students will learn how to use real-world data to perform climate change modeling and analysis through a case study of the warming temperature in the City of Qingdao, Shandong.