各位同学：

全英文课程《Spatial Data Analysis and R Practice》（空间数据分析与R语言实践）将在12月11日至12月14日开课，32个学时, 共计2个学分，课程形式为课堂讲授和上机实训，主讲教师为美国肯特州立大学叶信岳教授。叶信岳教授是美国肯特州立大学计算社会科学实验室创始主任、地理系博士生导师；著名开源时空分析软件STARS和Pysal的开发者之一；美国高校经济发展学会研究分析奖第一位得主和美国地理学会区域发展与规划学术新星奖第一位华人得主，CPGIS（国际华人地理信息科学学会）主席， Stochastic Environmental Research & Risk Assessment(SCI杂志)副主编。教学具体安排如下：

Dear Graduates:

The graduate course 《Spatial Data Analysis and R Practice》 will be taught by Prof. Xinyue Ye from Kent State University, USA, from Dec.11 to Dec.14, 2017. This course is 2 credits and has 32 credit hours. This course will be taught mainly as lecture and computer practice. The participants will have to present their homework on Thursday- Dec.14 in order to get their credit. Professor Xinyue Ye is the founding director of Computational Social Science Lab at Kent State University. His major expertise is on modelling the geographical perspective of socioeconomic inequality and human dynamics. His work won the national first-place award of "research and analysis" from the US University Economic Development Association in 2011 and he received the emerging scholar award from AAG’s Regional Development and Planning Specialty Group in 2012.He was elected to Chair of AAG Regional Development and Planning Specialty Group (2014-15), Co-Chair of AAG Asian Geography Specialty Group (2015-17), and President of International Association of Chinese Professionals in Geographic Information Science (2016-17).

The detailed class schedule is as follows.

December 11 (Monday)

8:00am-11:00am: Introduction to R and Spatial Data

Briefly introduce R as a powerful environment and programming language for the analysis of numerical data. Spatial data (also known as geospatial data or geographic information) is usually stored as coordinates and topology, and it can be mapped.

2pm-5pm: Data Visualization

Create data visualizations with just a couple of lines of code in R.

December 12 (Tuesday)

8:00am-11:00am: Exploratory Spatial Data Analysis: Lattice Data

Study lattice data to detect the neighborhood effects and spillovers. ESDA is a subset of exploratory data analysis (EDA) methods that focus on the distinguishing characteristics of geographical data and, specifically, on spatial autocorrelation and spatial heterogeneity.

2pm-5pm: Point Pattern Analysis

Point pattern analysis is the study of the spatial arrangements of points in (usually 2-dimensional) space.

December 13 (Wednesday)

8:00am-11:00am: Geostatistics

Geostatistics is a class of statistics used to analyze and predict the values associated with spatial or spatiotemporal phenomena. It incorporates the spatial (and in some cases temporal) coordinates of the data within the analyses.

2pm-5pm: Spatial Regression

Spatial regression methods capture spatial dependency in regression analysis, avoiding statistical problems such as unstable parameters and unreliable significance tests, as well as providing information on spatial relationships among the variables involved.

December 14 (Thursday)

8:00am-11:00am: Spatial Panel Regression

The main advantage of spatial panel regression is to examine both spatial and time effects in the regression.

2pm-5pm: Big Data and Spatial Network Analysis

Study spatial pattern of virtual network elements such as information diffusion and human behavior across space in the big data context.

课程名称：Spatial Data Analysis and R Practice

授课老师：Professor Xinyue Ye, USA, Kent State University

授课时间：Dec.11 to Dec.14, 2017

授课地点：逸夫楼A303 　Yifu Building A303

请有意向选修的留学生、研究生到理学院研究生管理办公室B221进行登记，电话027-87282199，请各位同学相互转告。

理学院

2017年12月4日