Dept. of Statistics
North Carolina State University
ST 524 Statistics in Plant Science 3(3-1-0)
FALL 2008
http://courses.ncsu.edu/st524
Class Wolfware site:
Course webpage:
http://www.stat.ncsu.edu/people/arellano/courses/st524/Fall08/
— Hours
: T, H 1:30 pm - 2:45 pm
— Instructor
: Consuelo Arellano, PhD
arellano@stat.ncsu.edu
— Office
: 4A Patterson Hall
Phone: (919) 515-1923
— Office hours
: MW 2:00 pm - 3:00 pm; TH 10:00 am-12 noon; or by appointment.
Room: HA 320
— Teaching Assistant: Pedro A. Torres, patorres@ncsu.edu
o
Office hours
: WF 8:00 am-9:00 am; or by appointment. Room 9 Patterson Hall.
— Pre requisite: ST512 or equivalent
— Computer Lab Hours: T. 3:00 pm - 4:15 pm - G100 HA – Statistics Instructional Computing Lab (SICL)
— Grading System:
• 2 Mid-terms
40%
• Homework Assignments 30%
• Final Exam
30%
— Text: None.
Dr. Cavell Brownie’s notes available at the NCSU Library Electric Reserves.
NCSU Electronic Reserves:
http://www.lib.ncsu.edu/reserves/
— References
o
Contemporary Statistical Models for the Plant and Soil Sciences, by O. Schabenberger and F.
J. Pierce. 1st ed. CRC Press (2002) SB91. S34 2002
o Planning, Construction, and Statistical Analysis of Comparative Experiments, by Francis G.
Giesbrecht and Marcia L. Gumpertz. Wiley. (2004) QA279 .G52 2004
o
Principles and Procedures of Statistics: a biometrical approach. R. G. D. Steel, J. H. Torrie
and D. A. Dickey. 3rd ed. Mc Graw Hill. (1997). QA276. S82 1997
o Statistical Principles of Research Design and Analysis, by R. O. Kuehl. Duxbury Press (1994)
Q182.3.K84 1994
o Practical Strategies for Experimenting, G. K. Robinson. Wiley (2000) QA279. R64. 2000
o Experimental Designs, by W. G. Cochran and G. Cox. 2nd ed. Wiley (1992) Q180 .A1 C6 1992
o
Statistical Methods, by G. W. Snedecor and W. G. Cochran. 8th ed. The Iowa State
University Press . (1989) QA 276.12.S59 1989
o Quick Start to Data Analysis with SAS. F. Dilorio and K. A. Hardy. 1st ed. Duxbury Press.
(1996) QA276.4 D548 1996
ST 524
1
Dept. of Statistics
o
North Carolina State University
SAS for Mixed Models, by R. C. Littell, G. A. Milliken, W. W. Stroup. R. D. Wolfinger and
O. Schabenberger. 2nd ed. SAS Press. (2006). QA276.4 .S22254 2006
ST 524 Statistics In Plant Science3(3-1-0) F Preq: ST 512 Principles and techniques of planning,
establishing and executing field and greenhouse experiments. Size, shape and orientation of plots;
border effects; estimation of size of experiments for specified accuracy; subsampling plots and yields
for laboratory analysis; combining data from a series of years and/or locations; rotation experiments;
repeated measures data; multiple comparisons in variety trial results; selection of predictors in
multiple regression; introduction to interspecies and intraspecies plant competition experiments and
models. Course Offerings: fall
Course Outline
1. Introduction
2. Field Experimentation: principles and practice
a. Field plot technique
b. Block and plot shape and orientation
c. Uniformity trials
d. (optimum plot size, Smith’s b)
3. Factorial treatment designs
a. Partitioning main and interaction effects
b. Orthogonal contrasts, planned comparisons
c. Orthogonal polynomial contrasts
4. Multiple comparisons procedures
a. Misuses
b. Comparison of procedures
5. Split-plot and related designs
a. Split-split plot designs
b. Advantages and disadvantages of split plot designs
c. Split block or stripped split plot designs
d. Standard errors of treatment contrasts.
6. Repeated Measures data
a. Measurement over time and space
b. Methods of analysis, repeated measures ANOVA
7. Experiments in greenhouses and growth chambers
ST 524
2
Dept. of Statistics
North Carolina State University
a. Replication over time
b. Replication of between and within-chamber treatments
8. Experiments in several years and /or locations
a. Combined ANOVA
b. Expected Mean Squares
c. Test for Treatment effects
9. Designs for trials with large number of treatments
a. Confounding in factorial designs
b. Incomplete Block Design. Lattice designs for variety trials.
10. Nonlinear regression
11. Analysis of covariance
12. Spatial analysis techniques
End-of-semester class evaluations
Schedule: Online class evaluations will be available for students to
complete during the last week of class the following dates and time:
Fall Session 8 a.m. November 21 through 8 a.m. December 8 Students will receive an email message directing them to a website where
they can login using their Unity ID and complete evaluations. All
evaluations are confidential; instructors will never know how any one
student responded to any question, and students will never know the ratings
for any particular instructors.
Evaluation website: https://classeval.ncsu.edu
Student help desk: classeval@ncsu.edu
More information about ClassEval: http://www2.acs.ncsu.edu/UPA/classeval/
Important Dates:
http://www.ncsu.edu/registrar/calendars/academicfall.html
Fall Break
: October 9-10
Last day to drop a course with tuition adjustment
: September 3
Last day to drop a course without a grade
: October 17
Thanksgiving Vacation (no classes)
: November 26 – 28
Thanksgiving Holiday (university closed)
: November 27 – 28
Dead Week
: December 1 - 5
Last Day of Classes
: December 5.
First Exam
: October 2, 2008
Second Exam
: November 20, 2008
Final Examination
: Tuesday, Dec 9, 2008, 1:00 - 4:00 p.m.
(http://www.ncsu.edu/registrar/calendars/examfall.html)
ST 524
3