課程資訊
課程名稱
生態研究法
RESEARCH METHODS IN ECOLOGY 
開課學期
98-2 
授課對象
生物資源暨農學院  昆蟲學系  
授課教師
奧山利規 
課號
ENT5053 
課程識別碼
632EU1150 
班次
 
學分
全/半年
半年 
必/選修
選修 
上課時間
星期四5,6,7(12:20~15:10) 
上課地點
中非105 
備註
本課程以英語授課。須先修習基礎統計。
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/982research_methods 
課程簡介影片
 
核心能力關聯
本課程尚未建立核心能力關連
課程大綱
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課程概述

本課程內容為實驗設計,主要著重於建立科學假設、設計實驗及獲得實驗結果。建議修本課程學生已具有基本實驗數據分析的能力。課程並包含部份有助於分析複雜生態資料之分析方法。 

課程目標
本課程目標為訓練學生獨立設計科學實驗、收集並分析數據以及判斷科學證據之能力。 
課程要求
須先修習基礎統計。 
預期每週課後學習時數
 
Office Hours
 
指定閱讀
 
參考書目
Experimental design for the life sciences. Second edition. By Greame D. Ruxton and Nick Colegrave. Oxford University Press, 2008. 
評量方式
(僅供參考)
   
課程進度
週次
日期
單元主題
Week 1
2/25  Course overview<br/>
An introduction to R
<br/><br/>
<b>Reading</b><br/>
Johnson (1999) [p-value]
<br/><br/>
<b>Homework</b><br/>
Go through the R introduction (Rintro.pdf).<br/>

<br/>
Assignment 1 (due 3/4 1pm) 
Week 2
3/04  Questions and Hypotheses<br/>
R intro.
<br/><br/>
Assignment 2 (due 3/10 1pm) 
Week 3
3/11  Between-individual variation, replication and sampling
<br/><br/>
<b>Reading</b><br/>
Hurlbert (1984) [Pseudoreplication]
<br/><br/>
Assignment 3 (due 3/18 1pm) 
Week 4
3/18  Experimental designs<br/>
<br/>
Assignment 4 (due 3/25 1pm) 
Week 5
3/25  Taking measurements
<br/><br/>
Assignment 5 (due 4/1 1pm) 
Week 6
4/01  Review of common statistical tests<br/>
General power analysis
<br /><br/>
Assignment 6 (due 4/8 1pm) 
Week 7
4/08  Exam 1 
Week 8
4/15  Sum of squares<br/>
Bootstrap
<br/><br/>
Assignment 7 (due 4/22 1pm) 
Week 9
4/22  Maximum likelihood<br/>
Likelihood ratio test<br/>
Profile likelihood
<br/><br/>
Assignment 8 (due 4/29 1pm)
 
Week 10
4/29  Generalized Linear Model (Poisson)
<br/><br/>
Assignment 9 (due 5/6 1pm)
 
Week 11
5/06  Generalized Linear Model (Binomial)
<br/><br/>
Assignment 10 (due 5/13 1pm)  
Week 12
5/13  Overdispersion<br/>
<br/>
Assignment 11 (due 5/20 1pm)  
Week 13
5/20  Zero-truncated and mixture models
<br/><br/>
Assignment 12 (due 5/27 1pm)  
Week 14
5/27  Parametric bootstrap likelihood ratio test
<br/><br/>
Assignment 13 (due 6/3 1pm)
 
Week 15
6/03  Generalized Linear Mixed Model
<br/><br/>
Assignment 14 (due 6/10 1pm)  
Week 16
6/10  Review 
Week 17
6/17  Final exam