PLS205

DESIGN, ANALYSIS, AND INTERPRETATION OF EXPERIMENTS

WINTER QUARTER 2008

 

Syllabus and General Information

 

COURSE GOALS
To introduce graduate students in the agricultural and environmental sciences to the research process and the statistical methods necessary to plan, conduct, and interpret effective experiments.

 

 

PREREQUISITE
AMR120 or equivalent (e.g. ASE120)

 

 

SOFTWARE

All labs, homework assignments, and exams will be structured around the SAS software package.

 

 

COURSE FORMAT AND GRADES
The course consists of two 1.5-hour lectures (Tuesday & Thursday, 9:00 am to 10:20 am, in Wellman 212) and one hour of discussion / computer laboratory (Thursday 4:10 pm to 5:00 pm or 5:20 to 6:10, in Hutchison 73) per week.  Grades are based on two exams, nine homework assignments / problem sets, and an optional extra credit project involving analysis and interpretation of students' experimental data:


                              Homework                       25%
                              First Exam                        35%       (due at the beginning of class on Tuesday, February 19)
                              Second exam                    40%      (due by 1 PM on Tuesday, March 18, in 267 Hunt Hall)
                              Extra credit project             2%       (due by 5 PM on Thursday, March 20, in 267 Hunt Hall)

 

 

TOPICAL OUTLINE
1.       Introduction to principles of experimental design
2.       Distributions, sampling, and hypothesis testing; calculation of sample size
3.       Fundamentals of ANOVA
4.       Orthogonal contrasts
5.       Mean separations
6.       Blocked designs
7.       Transformations
8.       Factorial analysis
9.       Unbalanced designs
10.     Fixed, random, and mixed models
11.     Split plot designs and repeated measures
12.     Covariance analysis (ANCOVA)
13.     Non-parametric methods


Click here for  SCHEDULE

 

 

COMPUTER RESOURCES
For on-campus computer room availability and hours of operation, click HERE

  • PES 1137                    Username: PLS205; Password: jorge; Door code: 70716
  • Hutchison 73
  • Meyer 1131
  • Recommended: purchase of SAS version for students in the bookstore

 

 

INSTRUCTOR

Jorge Dubcovsky.  E-mail: jdubcovsky@ucdavis.edu (752-5159).  Office hours Friday 4:00 pm to 6:00 pm, in Hunt 281.

 

TA
Iago Lowe.  E-mail: izlowe@ucdavis.edu.  Homework and SAS programming questions.  Office hours Monday 2:00 pm - 4:00 pm and Wednesday 9:00 am – 11:00 am, in PES 1137 (door access code 70716).

 

READER
Gina Darin.  E-mail: gmdarin@ucdavis.edu. Homework grading questions.  Office hours Monday 2:00 pm – 3:00 pm and Wednesday 9:00 am – 10:00 am, in PES 1137, and by appointment.

 

REQUIRED TEXT:
Principles and Procedures of Statistics. R.G.D. Steel, J.H. Torrie & D.A. Dickey. McGraw-Hill, Publisher, 3rd Edition, 1997.

 

The book is out of print, but we have obtained copyright permit from the Editor; copies may be found at the UCD bookstore.

 

Other useful references on Experimental Design:

  • Box, G. E. P.; Hunter, W. G.; Hunter, J. S. 1978. Statistics for Experimenters; An Introduction to Design, Data Analysis, and Model Building. Wiley.
  • Cochran, William G.; Cox, Gertrude M. (1957).  Experimental Designs. John Wiley and Sons, New York.
  • Little, Thomas M.; Hills, F. Jackson (1978).  Agricultural Experimentation. John Wiley, New York.
  • Snedecor, George W; Cochran, William G. 1980. Statistical Methods (7thEd.). The Iowa State University Press.
  • Sokal, Robert R.; Rohlf, F. James (1995) Biometry. (3rd Ed.) W.H. Freemanand Company. New York.

 

 

REFERENCES FOR SAS

Online references:
Help for SAS: http://www.agronomy.ucdavis.edu/agr205/onlinedoc.htm
Useful sections :
      SAS PROCEDURES GUIDE (e.g. Proc UNIVARIATE )
      SAS/STAT and ANALIST (good general introductions and detailed procedures descriptions)

 

Other SAS introductory texts:
Cody, Ronald P.; Smith, Jeffrey K. (1997).  Applied Statisticsand the SAS Programming Language. 4th Ed. Prentice Hall, New Jersey
Delwiche, Lora D.; Slaughter, Susan J. The Little SAS Book, a primer.1995. SAS Institute Inc., Cary, NC, USA.
Recommended: Littell, Ramon C.; Freund, Rudolf J.; Spector Philip C. SAS System for Linear Models. 3rd Ed. SAS Series in Statistical Applications.

 

 

Home | Syllabus and General Information | Course Schedule (Lectures, Labs, Assignments)  | Guide for Project

Available Computer Labs | Useful SAS links on Campus | Plant Sciences Home | UC Davis Home

Last updated:  December 2007