主讲教师：Dr.Travis Brenden 副教授

【授课时间、地点】

【课程简介】

R is a powerful and versatile data analysis package that can be freely available downloaded from the world-wide web. Students who complete this course will understand the benefits of using R and will be able to more easily transition to using R from other software packages. Topics will include how to install and use R libraries, importing data, graphing, writing loops and conditional statements, and creating user-defined functions.

【上课要求】

自带笔记本电脑。

【专家简况】

Dr. Travis Brenden is Associate Director of the Quantitative Fisheries Center at Michigan State University (MSU) and an Associate Professor in the Department of Fisheries and Wildlife at MSU.  Dr. Brenden received a B.S. in Biological Sciences from South Dakota State University and M.S. and Ph.D. degrees in Fisheries Science from Virginia Polytechnic Institute and State University (VPI&SU).  He additionally has an M.S. degree in Statistics from VPI&SU.   Prior to his employment at MSU, he was a Post-Doctoral Research Associate at the University of Michigan where he collaborated on a U.S. Environmental Protection Agency project concerning the development of stream classification systems and risk assessments for Midwestern U.S. rivers.  Dr. Brenden’s research focus at MSU is in the area of fish population dynamics, stock assessment, and modeling.  Research projects in which he is currently involved include the spatial estimation of mortality rates for walleye Sander vitreus in Lake Erie from a long-term jaw tagging dataset, the extension of genetic stock identification methods to account for temporal variability in spawning population contributions to the mixed stock, and the evaluation of harvest policy performance on the management of mixed stock fisheries.  Dr. Brenden has assisted in developing online courses on maximum likelihood estimation and the use of the R statistical computing and graphing system.  Additionally, Dr. Brenden has taught/co-taught short courses on the use of AD Model Builder and fishery stock assessment methodologies.