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Unformatted text preview: Crop Sciences 499 Applied Multivariate Methods Spring 2007 Instructors: Email Phone Office Germán Bollero [email protected] 3339475 W 201C Turner Hall Fernando Miguez [email protected] Office Hours: Germán Bollero Wednesday 35 PM Course Objective: 1) To understand the need, appropriateness, advantages, and limitations of multivariate methods. 2) To learn about the use of multivariate methods in the biological sciences. 3) To get familiar with multivariate methods in the Statistical Software SAS. 4) To introduce the statistical freeware R. Note: I encourage all students taking CPSC 440 to become familiar with the University of Illinois’ Code of Policies and Regulations Applying to All Students” and specifically “Academic Integrity” Rule 33 ( http://www.uiuc.edu/admin_manual/code/rule_33.html ). These regulations apply to all undergraduate, graduate, and professional students enrolled at the University of Illinois at UrbanaChampaign. EMAIL USE: You are welcome to contact your instructors using email. However, I strongly recommend posting questions about the class in the bulletin boards included in Compass ( https://compass portal.cites.uiuc.edu/login.html ). This will reduce overlapping and will increase interaction among students and instructors. Required Text: “Applied multivariate methods for data analysts”. D.E. Johnson. 1998.Duxbury Press. Recommended additional reading: Delwiche, L.D. and S.J Slaughter. 2003. The Little SAS Book, A primer. 3 rd Ed. SAS Institute Inc., Cary NC. Johnson, R.A., and D.W. Wichern. 2002. Applied multivariate statistical analysis. 5 th Ed. Prentince Hall, NJ. Khattree, R., and D.N. Naik. 1999. Applied multivariate statistics with SAS software. SAS Institute, Cary, NC, Wiley, NY. Anderson ,T.W. 2003. An Introduction to Multivariate Statistical Analysis. 3 rd Ed. Wiley, NY. Harris, R.J.. 2001. A primer of multivariate statistics. 3 rd Ed. Lawrence Erlbaum Associates Inc., NJ. 1 Searle, S.R. 1982. Matrix algebra useful for statistics. Ed. Wiley, NY. Grading scale: 92 % of the total points for the semester A 85 % of the total points for the semester B+ 80 % of the total points for the semester B 75 % of the total points for the semester C+ 70 % of the total points for the semester C 65 % of the total points for the semester D+ 60 % of the total points for the semester D Less than 60 % of the total points for the semester F Percentage distribution: Weekly homework 20% Due every week during lecture on Thursday One day late 10 % off, not accepted after 10 AM Friday Two Midterms First: . Onesided page of notes 15% (Fifth week of classes: February 15 th ) Second: Twosided page of notes 20% (Tenth week of classes: March 29 th ) NO MAKE UP EXAMS Final: Twosided page of notes 25% Special Project 20% 2 Topics: Introduction to multivariate statistical methods....
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