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 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:
Martin Quincke
Telephone: 737-5876
E-mail: Martin.Quincke@oregonstate.edu
Office: CRPS 221
Office Hours: W 9:00-10:00 - others by
appointment
Vidyasagar Sathuvalli
Telephone: 737-5464
E-mail: vidyasas@hort.oregonstate.edu
Office: ALS 4148
Office Hours: T 11:00-12:00 - others by
appointment
Required Text
There is no required text for this class.
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)
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. A copy is on reserve in the
library. QK51.C58 2001)
Cody, Ronald P. and Jeffrey K. Smith (1997) Applied Statistics and the
SAS Programming Language, 4th edition. Prentice Hall, New Jersey. (on reserve in
the library. QA276.4 .C53 1997)
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. 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_W2008.
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% |
| First exam | 15% |
| Second exam | 15% |
| Take-home design problem and SAS analysis | 15% |
| Proposal for experiment | 20% |
| 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. However, you will 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