Advanced
Statistics for Biologists
STT
814 Sections III & IV
Spring,
2012
COURSE: Statistics 814 – Advanced Statistics for Biologists
INSTRUCTOR: Dr. R.J. Tempelman
Department of Animal Science
1205J Anthony Hall
Tel: 355-8445 (or 5-8445 from a campus phone)
e-mail: tempelma@msu.edu
TEACHING ASST: Xiaoqing Zhu (zhuxiaoq@msu.edu)
OFFICE HOURS: Tempelman: Monday 11:20 a.m.-12:00 p.m.
Thursday 3:20 p.m.- 4:00 p.m.
If at all possible, please call ahead as I am sometimes called away to various meetings.
LECTURE: 10:20-11:10 Mondays, Wednesdays, and Fridays
Room 155 Communication Arts Building
SECTION 3 LAB: 1:00
– 2:50 Thursdays, 222 South Kedzie
SECTION 4 LAB: 3:00
– 4:50 Thursdays, 222 South Kedzie
TEXTS:
Required:
·
Applied Linear
Statistical Models, Fifth Edition (2005) by M.H. Kutner,
C.J. Nachtsheim, J. Neter,
and W. Li., McGraw-Hill
Recommended:
·
SAS System
for Regression, Third Edition (2000) by R.J. Freund and R.C. Littell. SAS Publishing (http://support.sas.com/publishing/bbu/companion_site/57313.html
) ISBN:978-1-58025-725-1.
·
SAS System for Mixed Models, Second Edition (2006) by R.J. Littell, G.A. Milliken, W.W.
Stroup, R.D. Wolfinger, and O. Schabenberger. SAS Publishing (http://support.sas.com/publishing/bbu/companion_site/59882.html
) ISBN: 978-1-59047-500-3.
·
Analysis of Messy Data, Volume 1. Designed Experiments (2009) by G.A. Milliken and D.E. Johnson. CRC
Press, Boca Raton, FL ISBN-13:978-1-58488-334-0.
GRADING PROCEDURE:
Hourly Test (~February 24, 2011) ..….……...…………………………….....…….…20%
Take-home Test (handed out early April, due within 48 hours)...............................…25%
(Bi)Weekly Laboratory Assignments………….............................……………......….30%
Final Examination (2 hours Friday May 4, 2011 @ 10:00 a.m.)..........................…25%
The first test will
be in class. The second test will be a take-home test due by the subsequent
class period
HOMEWORK GRADING:
Xiaoqing Zhu (zhuxiaoq@msu.edu) will serve as the homework grader for the course. If you have questions on pending homeworks, please ask me. If you have questions about the grading of your homework, please first consult the homework key (uploaded to ANGEL after the grades are assigned) before checking with Xiaoqing. If you still have questions after all that, then please consult with me.
OBJECTIVE:
To enhance the student's statistical and software-intensive toolbase for the design and analysis of experimental and observational research data in the biological sciences.
COURSE CATALOG DESCRIPTION:
Concepts of reducing experimental error: covariance, complete and incomplete block designs, latin squares, split plots, repeated-measures designs, regression applications, and response surface designs.
CLASS
TOPIC SCHEDULE:
TOPIC |
APPROXIMATE NUMBER OF
LECTURES |
Introduction: Scientific
inquiry and the linear model |
1 |
Regression Linear
regression and residual diagnostics
review, Lack-of-fit hypothesis testing Matrix
algebra and modelling Introduction
to multiple linear regression Modelling response surfaces Type
I /Type III sums of squares Multiple
regression influence/diagnostics |
13 |
Factorial Designs Completely
randomized designs Two-factor
analysis of variance Multifactor
analysis of variance Regression
approach to factorial designs Analysis
of covariance Power
assessments |
9 |
Blocking Designs Randomized
Block Designs Incomplete
Block Designs |
7 |
Hiearchical Designs Nested
designs and Subsampling Repeated
Measures Analysis Mixed
effects models |
7 |
"Efficient" Designs Crossover
Designs |
6 |
TENTATIVE
LABORATORY SCHEDULE:
WEEK |
TOPIC |
1 |
Data
Management and Editing using SAS and Introduction to Regression Analysis
Using SAS PROC REG |
2 |
Regression
Analysis and Diagnostics using SAS PROC REG |
3 |
Matrix
Algebra using SAS PROC IML |
4 |
Multiple
Regression Analysis and Diagnostics using SAS PROC REG |
5 |
Response
Surface Designs and Analysis using SAS PROC RSREG |
6 |
Completely
randomized designs using SAS PROC GLM |
7 |
Factorial
Design Analysis using SAS PROC GLM/GLIMMIX (Part I) |
8 |
Factorial
Design Analysis using SAS PROC GLM GLIMMIX (Part II) |
9 |
Analysis
of Covariance using SAS PROC GLM/GLIMMIX - Power Analysis for Experimental
Designs |
10 |
Analysis
of Randomized Block Designs using SAS PROC MIXED/GLIMMIX |
11 |
Power
Analyses |
12 |
Analysis
of Split Plot and Repeated Measures Designs using SAS PROC MIXED/GLIMMIX |
13 |
Analysis
of Replicated Latin Squares and Crossover designs using SAS PROC
MIXED/GLIMMIX |
The
statistical software SAS will form a major component of the data analysis
training in this course. Example SAS programs and datasets required for labs
will periodically be available on the course MSU ANGEL webpage (www.angel.msu.edu)