106學年第1學期課程綱要 |
@尊重智慧財產權,請同學勿隨意影印教科書 。 Please respect the intellectual property rights, and shall not copy the textbooks arbitrarily. |
一、課程基本資料 |
開課序號 | 2856 | 課程學制 | |
科目代碼 | BIC9035 | 課程名稱 | R程式語言與生態演化分析 |
英文名稱 | Data Analysis for Ecology and Evolution in R Programming Language | ||
全/半年 | 半 | 必/選修 | 選修 |
學分數 | 3.0 | 每週授課時數 | 正課時數: 3 小時 |
開課系級 | 生科系(學)大碩合開 | ||
先修課程 | |||
課程簡介 | This course will introduce multivariate and spatial statistical techniques for analysis of ecological data using R programming language. Bioconductor work flow for high-throughput sequence analysis will also be covered. The details of R functions and scripts in relation to various types of multivariate, spatial and sequence analyses will be described in lecture. Homework assignments with various types of ecological and evolutionary data will be made available to students. | ||
課程目標 | 對應系所核心能力 | ||
1. To understand the logical basis and computational principles of various R functions | 學士: 1-1 具備生命科學之專業知識 3-1 具備正確的科學態度,能主動探索生命科學之相關議題,並瞭解遵守科學倫理之重要性 |
||
2. To understand and perform statistical tests and graphical examination of multivariate data | 學士: 1-1 具備生命科學之專業知識 3-1 具備正確的科學態度,能主動探索生命科學之相關議題,並瞭解遵守科學倫理之重要性 |
二、教學大綱 |
授課教師 | 黃士穎 | ||
教學進度與主題 | |||
1. Introduction, R, RStudio, Bioconductor and R GUI 2. Data characteristics and data frames 3. Graphical and tabular examination of multivariate data 4. Functions, simple programming and model formulae 5. Probability distributions, normality and summary statistics 6. Statistical hypothesis testing 7. Regression fitting models 8. Ecological analysis 9. Midterm examination 10. Species and community distribution models 11. Cluster analysis and Ordination 12. Phylogenetic diversity 13. Community structure and trait evolution 14. Multivariate analysis of genetic and environmental variables 16. Map drawing and Species distribution modeling 17. R/Bioconductor in high-throughput sequence analysis |
|||
教學方法 | |||
方式 | 說明 | ||
講述法 |   | ||
討論法 |   | ||
問題解決教學 |   | ||
實驗/實作 |   | ||
評量方法 | |||
方式 | 百分比 | 說明 | |
作業 | 50 % |   | |
期中考 | 25 % |   | |
期末考 | 25 % |   | |
參考書目 |
1.A beginner’s guide to R. Zurr, Ieno, Meesters,Springer, 2009. 2. Analysing ecological data. Zuur, Ieno, and Smith. Springer 2009. 3. Introductory statistics with R. Dalgaard. Springer, 2008. 4. Biocondcutor case studies, Hahne, Huber, Gentleman, and Falcon, Springer, 2008. |