課程資訊
課程名稱
 生態研究法
Research Methods in Ecology 
開課學期
 106-2 
授課對象
 生物資源暨農學院  昆蟲學研究所  
授課教師
 奧山利規 
課號
 ENT5053 
課程識別碼
 632EU1150 
班次
  
學分
 3.0 
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
 本課程以英語授課。上課教室：永齡生醫工程館421室。建議先修習基礎統計學。
限學士班三年級以上
總人數上限：16人 
Ceiba 課程網頁
 http://ceiba.ntu.edu.tw/1062ENT5053 
課程簡介影片
 
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課程概述

This is a course in experimental design and data analysis. Computer simulations will be used to understand the concepts of various statistical tests, but no prior experience in programming is required. The experimental design part of the course will use a textbook (see below). The main theme of the data analysis part of the course is the maximum likelihood method although other approaches are also discussed. The computer language R (http://www.r-project.org/) will be used. Expectations

  • Ask questions, in or out of class, when you don’t understand something. If you are confused, you are probably not the only one.
  • Assignments will be given nearly every week. Students must work on assignments on their own. Understanding a provided solution and deriving it by yourself are not the same (especially for programming). To discourage students from copying assignments (which has been very common in past years), assignments are not graded. Even if students have the perfect assignments (i.e., 100% if graded), the assignments have no influence on their grades. Nonetheless, successful completions of assignments are essential for the successful completion of the course. Students are encouraged to seek out the instructor for help when they have troubles completing assignments. Grading Exam 1 40% Exam 2 60% (cumulative) Bonus points Bonus points will be calculated based mainly on attendance and participation (e.g., asking questions). Two absences or four tardinesses will result in 0 bonus points (a tardiness over 20 min is regarded as an absence). Poor class participation (e.g., playing with a cell phone/computer, sleeping, etc.) is considered an absence. Even when a student has a valid reason for an absence, it is considered as an absence because attendance only affects bonus points. The maximum possible bonus points are 10% (to final % grade), but undergraduate student whose grades are less than 60% (final grade without bonus points) can get at most 60% (final grade with bonus points). Graduate student whose grades are less than 70% (final grade without bonus points) can get at most 70% (final grade with bonus points). Schedule The schedule (shown in the content section of this website) is subject to change. 

    • 課程目標
    		 . 
    課程要求
    		  
    預期每週課後學習時數
    		  
    Office Hours
    		  
    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
    Week 1
    		 3/01  Course overview<br/>
    Statistics review 
    Week 2
    		 3/08  Starting with a well-defined hypothesis </br>
    Selecting the broad design for your study<br/></br>

    The section on "Controls" will be discussed in a different week.
     
    Week 3
    		 3/15  Between-individual variation, replication and sampling<br/>
    Pseudoreplication<br/>
    Power analysis 
    Week 4
    		 3/22  Different experimental designs 
    Week 5
    		 3/29  Taking measurements  
    Week 6
    		 4/05  no class (spring break) 
    Week 7
    		 4/12  Review 
    Week 8
    		 4/19  Exam 1 
    Week 9
    		 4/26  Sum of squares<br/>
    Numerical optimization<br/>
    Bootstrap  
    Week 10
    		 5/03  Maximum likelihood<br/>
    Likelihood ratio tests 
    Week 11
    		 5/10  Maximum likelihood review  
    Week 12
    		 5/17  Generalized Linear Models (GLMs)

    Poisson GLM

    Dummy variables 
    Week 13
    		 5/24  Binomial GLM

    Offset

    Gamma GLM 
    Week 14
    		 5/31  Overdispersion<br/>
    Quasilikelihood<br/>
    Negative binomial GLM 
    Week 15
    		 6/07  Customizing models 
    Week 16
    		 6/14  Generalized Linear Mixed Models (GLMMs) 
    Week 17
    		 6/21  Review 
    Week 18
    		 6/28  Exam 2