課程資訊
課程名稱
統計生態學與程式語言應用
Computer Intensive Statistics in Ecology 
開課學期
102-2 
授課對象
學程  海洋科學學程  
授課教師
謝志豪 
課號
Ocean5052 
課程識別碼
241EU1920 
班次
 
學分
全/半年
半年 
必/選修
選修 
上課時間
星期四2,3,4(9:10~12:10) 
上課地點
 
備註
教室地點:計中212教室。與王慧瑜合開
總人數上限:25人 
Ceiba 課程網頁
http://ceiba.ntu.edu.tw/1022EcoStat 
課程簡介影片
 
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課程概述

THIS IS AN ADVANCED COURSE INTENDED FOR SENIOR UNDERGRADUATE AND GRADUATE STUDENTS WITH KNOWLEDGE OF BASIC STATISTICS INCLUDING RANDOM VARIABLES, ANALYSIS OF VARIANCE, REGRESSION ANALYSIS, AND RANK-BASED NON-PARAMETRIC STATISTICS. WE WILL DISCUSS SEVERAL COMPUTER-INTENSIVE STATISTICAL METHODS. WE WILL DISCUSS THE THEORY, ASSUMPTION, AND APPLICATION OF THESE METHODS IN ECOLOGICAL PROBLEMS. THE COURSE IS DESIGNED FOR HAND-ON WORK. STUDENTS NEED TO GET FAMILIAR WITH AT LEAST ONE COMPUTER LANGUAGE TO DO THE STATISTICS. MOST OF WORK CAN BE DONE WITH MATLAB, BUT ANY OTHER PROGRAMMING LANGUAGE WILL DO EQUALLY WELL. SOMETIMES, WE WILL USE WELL-DEVELOPED SOFTWARE WHEN THE COMPUTATION IS TOO COMPLICATED AND BEYOND THE BASIC LEVEL. THERE WILL BE DEDICATED TIME EVERY WEEK FOR STUDENTS TO PRESENT THEIR WORKS AND TO DISCUSS THE APPLICATION OF THESE METHODS ON REAL WORLD PROBLEMS. THE TOPICS MAY INCLUDE:
1. INTRODUCTION TO RANDOM VARIABLES
2. DISTRIBUTION AND RANDOM NUMBER GENERATOR
3. DIMENSION REDUCTION METHODS
4. MONTE CARLO METHOD
5. PERMUTATION, BOOTSTRAP, JACKKNIFE, SUB-SAMPLING AND RE-SAMPLING
6. INTERPOLATION, OPTIMIZATION, MINIMIZATION,
7. MAXIMUM LIKELIHOOD
8. CATEGORICAL AND REGRESSION TREE
9. KERNEL SMOOTHING
10. SIMPLE NEURAL NETWORK
11. MISSING DATA
12. STOCHASTIC TIME SERIES ANALYSIS
13. SPECTRAL ANALYSIS
14. FRACTAL
15. NONLINEAR TIME SERIES ANALYSIS
 

課程目標
The objectives are to provide students computational skills for sophisticated statistical methods that are often required for biological questions. 
課程要求
Students need to get familiar with at least one computer language to do the statistics. There will be dedicated time every week for students to present their works and to discuss the application of these methods on real world problems. 
預期每週課後學習時數
 
Office Hours
另約時間 
指定閱讀
 
參考書目
 
評量方式
(僅供參考)
   
課程進度
週次
日期
單元主題
無資料