課程資訊
課程名稱
 試驗設計在園藝的應用
EXPERIMENTAL DESIGN FOR HORTICULTURAL RESEARCH 
開課學期
 96-2 
授課對象
 學程  生物統計學程  
授課教師
 張龍生 
課號
 HORT5034 
課程識別碼
 628 U1700 
班次
  
學分
 3 
全/半年
 半年 
必/選修
 選修 
上課時間
 星期三2,3,4(9:10~12:10) 
上課地點
 園藝R205 
備註
 總人數上限：20人 
  
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

1. Physical performance of the experiment.
2. Linear model associated with that experiment.
3. Analysis of variance.
4. Expected mean squares.
5. Test of significance. 

課程目標
 You will be capable of doing such following things in the end of the class, hopefully.
1. Doing computation for any balanced analysis of variance regardless of whether you have seen that exact form before.
2. From a description of procedure of an experiment, be able to write the form of analysis of variance or equivalently write the linear model.
3. From an analysis of variance, be able to recognize the implications as to how the experiment was performed, i.e., restriction on the randomization.
4. Given certain questions to be answered experimentally and the available resources, design an experiment to restrict extraneous sources of variability, provide unbiased estimates of treatment effects and proper estimates of errors.
5. Use any of number of techniques to extract and interpret information from treatment. 
課程要求
  
預期每週課後學習時數
  
Office Hours
 每週三 12:20~13:50 
指定閱讀
  
參考書目
 Steel, R. G. D. and J. H. Torrie Principles and procedures of statistics. McGraw-Hill Book Co., N. Y. 
評量方式
(僅供參考)
  
No.
項目
百分比
說明
1. 
 Mid exam 
30% 
  
2. 
 Final exam 
30% 
  
3. 
 Homework 
20% 
  
4. 
 Other 
20% 
  
 
課程進度
週次
日期
單元主題
第1週
 2/20  I.Introduction 
第2週
 2/27  II.Principles of Experimental Design
What is an experiment?
Experimental unit and treatment
Experimental error
 
第3週
 3/05  II.Principles of Experimental Design
Replication and function
.Factors affecting the numbers of replication

 
第4週
 3/12  III.III. Analysis of Variance: one-way classification
1. The completely random design
2. The linear additive model
 
第5週
 3/19  IV. Analysis of Variance: one-way classification
3. Analysis of variance with sub-samples
4. Variance components in planning experiments
 
第6週
 3/26  IV. Analysis of Variance: one-way classification
1. introduction
2. L.S.D.
3. Tukey Test
 
第7週
 4/02  V. Analysis of Variance: one-way classification
4. S-N-K Test
5.Duncan Multiple Range test
6. Scheffe’s test
7. Choices
 
第8週
 4/09  VI. Nested analysis of variance
1. Nested anova design
2. computation
 
第9週
 4/16  VI. Nested analysis of variance
3. Nested anova with unequal sample sizes
4. The optimal allocation of resources
 
第10週
 4/23  VII. Analysis of Variance: Multi-way classification
1. The randomized complete block design
(1). Layout ant AOV
(2). Missing data
 
第11週
 4/30  VII. Analysis of Variance: Multi-way classification
(3). Estimate gain in efficiency
(4). Linear model
(5). Tukey’s non-additivity test
 
第12週
 5/07  2. Latin squares
(1). Layout ant AOV
(2). Estimate gain in efficiency
(3). Linear mode
 
第13週
 5/14  VIII. Orthogonal comparison test
1. Introduction
2. Contrast
3. ANOVA
 
第14週
 5/21  X. Analysis of Variance: Factorial experiments
1. Introduction
2. Simple effect, main effect, and interaction estimate
3. 2 x 2 factorial
 
第15週
 5/28  Analysis of Variance: Factorial experiments
4. 3 x 3 factorial
5. 3 x 3 x 3 factorial
6. Linear additive model
 
第16週
 6/04  XI. Analysis of Variance: Split-plot design
1. Introduction
2. Split-plot design
3. AOV
 
第17週
 6/11  XI. Analysis of Variance: Split-plot design
4. Linear model
5. Split-block design
 
第18週
 6/18  XII. Expecting mean squares
1. C. R. D.
2. R. C. B. D.
3. L. S.
4. Split-plot design