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Experimental Design and Statistical Analysis 
Lecturers: Drs. Jiankang Wang and Huihui Li Time of class: 8:00am11:00am, Tuesday, Classroom No. 17, September 2016  January 2017, The CAAS Graduate School Contents Lecture 1 (Sep. 20): Principles of design, probability and statistics. Three principles of experimental design, common designs, basic probability and statistics. [Lecture] [Class exercise] Lecture 2 (Sep. 27): Population and its distribution. Random variables, discrete distribution, continuous distributions, mean, variance and covariance of random variables etc. [Lecture][Class exercise] [Exercise of Lectures 1 and 2] [Answers] Lecture 3 (Oct. 11): Sampling and sampling distributions. Principles of sampling and sampling methods, sampling distributions, parameter estimations etc. [Lecture] [Class exercise] Lecture 4 (Oct. 18): Hypothesis testing. Test of population mean, test of population variance, test of a proportion, power of a test, suitable sample size etc. [Lecture][Class exercise] [Exercise of Lectures 3 and 4] [Answers] Lecture 5 (Oct. 25): Single factor design and analysis. Completely randomized design and its analysis, Complete randomized block design (RBD), analysis of variance (ANOVA) of RBD, multiple test, test of normality and homogeneity, data transformation, and incomplete design etc. [Lecture][Class exercise] Lecture 6 (Nov. 1): More on Complete Randomized Block Design (RBD). Multiple test, test of normality and homogeneity, data transformation etc. [Lecture] [Class exercise] [Exercise of Lectures 5 and 6] [Answers] Lecture 7 (Nov. 8): Multifactor design and analysis. Factorial treatment design and analysis, nested design and analysis etc. [Lecture] [Class exercise] Lecture 8 (Nov. 15): Latin square design and incomplete block design. Latin square design and analysis, incomplete block design and analysis etc. [Lecture] [Class exercise] Lecture 9 (Nov. 22): Orthogonal design and analysis. Linear model of ANOVA, orthogonal design and its analysis etc. [Lecture] [Exercise of Lectures 7, 8 and 9] [Class exercise] [Answers] Lecture 10 (Nov. 29): Categorical data and tests of goodnessoffit. Nonparametric statistics, tests of goodnessoffit, categorical data and its analysis etc. [Lecture] [Class exercise] Lecture 11 (Dec. 6): Correlation and regression. Correlation analysis, linear regression analysis, multiple linear regression, collinearity, model selection in regression [Lecture] [Analysis Tools in Excel] [Class exercise] [Exercise of Lectures 10 and 11] [Answers] Lecture 12 (Dec. 13): Introduction to genetic data analysis: I. Linkage Analysis Three point analysis, mapping functions, construction of genetic linkage maps, use of the integrated software QTL IciMapping. [Lecture] [QTL IciMapping Software] Lecture 13 (Dec. 20): Introduction to genetic data analysis: II. Linkage Maps. Three point analysis, mapping functions, construction of genetic linkage maps, use of the integrated software QTL IciMapping [Lecture][Exercise of Lectures 12 and 13] [Answers] Lecture 14 (Dec. 27): Introduction to genetic data analysis: II. Gene Mapping. Single marker analysis, simple interval mapping, use of the integrated software QTL IciMapping [Lecture] Lecture 15 (Dec. 27): Introduction to genetic data analysis: IV. Advanced Gene Mapping. Inclusive composite interval mapping, use of the integrated software QTL IciMapping [Lecture][Exercise of Lectures 14 and 15] [Answers] Jan. 10 (to be organized by the Graduate School): Final examination (2 hours). You can use your computer, class notes, and any reference books. You are on your own. No discussion is allowed. References 1. Dean A and D. Voss. 1999. Design and Analysis of Experiments. Springer, New York, NY, USA 2. Robert O. Kuehl. 2000. Design of Experiments: Statistical Principles of Research Design and Analysis, second edition. Duxbury Thomson Learning, Pacific Grove, CA, USA [pdfCh0] [pdfCh12] [pdfCh34] [pdfCh5Ch6] [pdfCh7Ch8] [pdfCh910] [pdfCh1112] [pdfCh1315] [pdfCh1617] [pdfCh1819] 3. Gerry P. Quinn and Michael J. Keough. 2002. Experimental Design and Data Analysis for Biologists. Cambridge University Press, Cambridge, UK [pdfCh1] [pdfCh2] [pdfCh3] [pdfCh4] [pdfCh5] [pdfCh6] [pdfCh7] [pdfCh8] [pdfCh9] [pdfCh10] [pdfCh11] [pdfCh12] [pdfCh13] [pdfCh14] [pdfCh15] [pdfCh16] [pdfCh17] 4. Morris H. DeGroot and Mark J. Schervish. 2012. Probability and Statistics (Fourth Edition). China edition published by Pearson Education Asia LTD., and China Machine Press, Beijing, China 5. Nanjing Agricultural University. 1991. Field Experiments and Statistical Methods. Agricultural Press, Beijing, China (in Chinese) 南京农业大学主编, 1991. 《田间试验和统计方法》. 农业出版社, 北京 6. Mao Shisong, Zhou Jixiang and Cheng Ying. 2004. Design of Experiment (in Chinese). China Statistics Press, Beijing, China (in Chinese) 茆诗松, 周纪芗, 陈颖主编, 2004. 《试验设计》. 中国统计出版社, 北京 7. Li Zhonglai, Liu Laifu and Cheng Shu Xiao. 2007. Biometrics (Second Edition). Beijing Normal University Publishing Group, Beijing, China (in Chinese) 李仲来, 刘来福, 程书肖编著. 《生物统计》. 北京师范大学出版集团, 北京 Course evaluation Class assignments (40%) + Final examination (60%) Requirement: Bring your computer to the class
