STAT4120/STAT8120

Applied Experimental Design

 

Course Description: Methods for constructing and analyzing designed experiments are considered.  The concepts of experimental unit, randomization, blocking, replication, error reduction and treatment structure are introduced.  The design and analysis of completely randomized, randomized complete block, incomplete block, Latin square, split-plot, repeated measures, factorial and fractional factorial designs will be covered.  Statistical software packages such as JMP, MINITAB, SAS or SPSS will be used.

 

Text: Design and Analysis of Experiments, Sixth Edition by Douglas C. Montgomery, New York: John Wiley and Sons, 2004.

 

Statistics for Experimenters: Design, Innovation and Discovery, Second Edition by George E. P. Box, J. Stuart Hunter and William G. Hunter, New York: John Wiley and Sons, 2005.

 

Prerequisite: STAT 7010 / STAT 7020                 

 

Computer Software: One or more of the following Statistical Software packages and student guides will be used in the course:

 

1) JMP – JMP for Basic Univariate and Multivariate Statistics: A Step-by-Step Guide by Ann Lehman, Norm O’Rourke, Larry Hatcher and Edward Stepanski, Cary, NC: SAS Institute, Inc., 2005.

 

2) MINITAB – The Student Guide to MINITAB Release 14, by John D. McLenzie and Robert Goldman, New York: Addison-Wesley, 2005.

 

3) SAS – Step-by-Step Basic Statistics Using SAS by Larry Hatcher (Student Guide and Exercises) Cary, NC: SAS Press, 2003.

 

The Little SAS Book by Lora Delviche and Susan Slaughter, Cary NC: SAS Press, 1996.

 

4) SPSS – How to Use SPSS: A Step-by-Step Guide to Analysis and Interpretation (Third Edition) by Brian C. Cronk, Los Angeles, CA: Pyrczak Publishing, 2004

 

Learning Outcomes: Upon satisfactory completion of this course, students will be able to:

 

1) Design appropriate experiments given the objectives of a study and constraints on the conduct of the experiment

 

2) Recognize the designs studied and correctly analyze data from them by

            a) using the appropriate model

            b) estimating treatment means, contrasts, standard errors and confidence intervals

            c) testing appropriate hypothesis about contrasts

            d) using appropriate graphical techniques

 

3) Choose among competing designs and evaluate an experimental protocol

 

4) Determine sufficient sample size

 

5) Interpret results in non-technical language explaining the benefits and limitations of the design

 

6) Describe the design, the analysis and the results clearly in writing and orally.