Additional links will be activated as the term progresses.
Announcements will be posted on the Blackboard as needed.
Time and Place:
Lectures: MWF 8:00 CRPS 122
Recitation: Thurs 8:00 - 9:20 or 9:30-10:50, CRPS 150
Instructor: Jennifer Kling
Telephone: 737-8277
E-mail: jennifer.kling@oregonstate.edu
Office: CRPS 249
Office Hours: MWF 9:30-10:30 - others by appointment
Teaching Assistants:
Guomei Wang
Telephone: 737-5839
E-mail: Guomei.Wang@oregonstate.edu
Office: CRPS 445
Office Hours: Tuesday 9:00-10:00
Miles Barrett
Telephone: 503 536-5054
E-mail: barretm@hort.oregonstate.edu
Office: ALS 4114
Office Hours: Tuesday 12:00-1:00
Required Text
There is no required text for this class. Recommended references are on reserve in the library.
Recommended References
Kuehl, Robert O. (2000) Design of Experiments: Statistical Principles of Research Design and Analysis, 2nd edition. Duxbury Press. (an excellent general reference, but uses slightly different notation than we do in class) Q182.3.K84 2000
Clewer, A.G. and D. H. Scarisbrick (2001) Practical Statistics and Experimental Design for Plant and Crop Science. John Wiley & Sons. (A good reference for those who are not too familiar with statistics; the emphasis on agricultural research is also very relevant for the course) QK51.C58 2001
Cody, Ronald P. and Jeffrey K. Smith (2006) Applied Statistics and the SAS Programming Language, 5th edition. Prentice Hall, New Jersey. QA276.4 .C53 2006
Petersen, Roger G. (1994) Agricultural Field Experiments: Design and Analysis. Marcel Dekker, New York. (Much of the lecture material was adapted from this text, but it contains some errors. Two copies of the text are on reserve in the library, should you need any clarification on lecture material.) S540.F5 P47 1994
Other Suggested References:
Cochran, W. G., and G. M. Cox (1957). Experimental Designs, 2nd ed., Wiley, New York.
Cox, D. R. (1958). Planning Experiments, Wiley, New York.
Gomez, K. A. and A. A. Gomez (1984). Statistical Procedures for Agricultural Research, 2nd ed. Wiley, New York.
Little, T. M., and F. J. Hills (1978). Agricultural Experimentation, Wiley, New York.
Montgomery, Douglas C. (1991). Design and Analysis of Experiments, 3rd ed., Wiley, New York.
Petersen, R. G. (1985). Design and Analysis of Experiments, Marcel Dekker, New York.
Snedecor, G. W., and W. G. Cochran (1980). Statistical Methods, 7th ed., Iowa State University Press, Ames, IA.
Steel, R. G. D., J. H. Torrie and D.A. Dickey (1997). Principles and Procedures of Statistics, 3rd ed., McGraw-Hill, New York.
Other SAS References:
Der, G. and B.S. Everitt (2002). A Handbook of Statistical Analyses using SAS, 2nd ed., Chapman & Hall/CRC.
Littell, R. C., W. W. Stroup, and R. J. Freund (2002). SAS for Linear Models, 4th ed. SAS Series in Statistical Applications.
Online Resources
For information on how to access and use the Blackboard, go to the OSU Extended Campus website login page at http://my.oregonstate.edu/
Grades for homework and exams will be posted on the Blackboard under CSS_590_001_W2009.
You can access the course website through the Blackboard (click on the course information button) or directly at this url:
http://cropandsoil.oregonstate.edu/classes/css590/
General Course Description
This course addresses the needs of the student preparing for a career in agricultural research or consultation and is intended to assist the scientist in the design, plot layout, analysis and interpretation of field and greenhouse experiments. Emphasis is placed on experimental designs used in agronomy and plant breeding research with more emphasis toward applied statistics rather than statistical theory. Many numerical examples and problems will be presented and the recitation will allow students to explore analysis using SAS and Excel.
Prerequisites
Students should have an introductory understanding of statistical methods including the ideas of interval estimation, significance testing, simple linear regression and correlation. Familiarity with such common statistical tables as Student’s t, F, and chi-square is expected. The necessary mathematical background is minimal. At most, a knowledge of college algebra is required.
Assessment/Evaluation of Student Performance
| Weekly assignments | 20% |
| Recitations | 10% |
| First exam | 10% |
| Second exam | 15% |
| Take-home design problem and SAS analysis | 15% |
| Proposal for experiment | 15% |
| Final exam | 15% |
| Total | 100% |
Grades will be assigned according to the following point system:
| 97-100 = A+ | 87-89 = B+ | 77-79 = C+ | 67-69 = D+ | <=59 = F |
| 93-96 = A | 83-86 = B | 73-76 = C | 63-66 = D | |
| 90-92 = A- | 80-82 = B- | 70-72 = C- | 60-62 = D- |
Assignments
There will be eight graded assignments in this class, which will be due one week after they are assigned. It is highly recommended that you use Excel to complete the assignments, and that you submit them electronically via the Assignment function in Blackboard. Use of Excel and Blackboard will be demonstrated in your recitation section during the first week of class.
You will not be expected to turn in work from your recitation sections. Self-assessments will be available on Blackboard to encourage you to review the lab material and ensure that you have understood the major concepts presented each week. You will also need to be able to write simple SAS programs in order to do your take-home design problem, and you may be asked to interpret SAS output on exams.
Instructional Objectives and Student Learning Outcomes:
Upon completion of the course, students should be able to:
Outline of Topics Covered
Tentative Recitation Schedule
Week 1 Introduction to Excel; review of basic statistics
Week 2 Introduction to SAS
Week 3 One-Way ANOVA (CRD); Two-way ANOVA (RBD)
Week 4 Subsampling; Transformations
Week 5 Latin Square ANOVA; Factorials
Week 6 Regression and Contrasts
Week 7 Split Plot, Strip Plot, Repeated Measures
Week 8 Multiple Comparison Tests, Augmented Designs
Week 9 Incomplete Block Designs
Week 10 Across Site Analyses, Mixed Models
