Last update: February 9, 2014: Design illustrations. e.g. Latin Square Split-Plot Why build this site?
Guides completed: CRD Single Factor
RCBD Single Factor
Guides in progress: See Analyze an Experiment table
to give an introduction to using SAS for statistical analysis
to guide students and researchers in identifying the proper
experimental and treatment designs for their study
to provide SAS macros (easily used collections of program statements)
the analyses covered by DAWG, customized for your experimental data
to guide users in stepwise fashion through each step of the SAS
analysis and interpretation of output
DAWG assumes some understanding of statistics and prior exposure to experimental design.
It is based on SAS v. 9.3.
Our goal is to develop individual guides (modules) for the experimental designs most used in agricultural and biological research, with a key to assist in selecting proper design:
Completely randomized design (CRD)
Randomized complete block design(RCBD)
Latin square design (LSD)
Multiple square latin square design MS-LSD)
Incomplete block design
Users may "customize" each of the seven ANOVA experimental designs with one of seven treatment designs:
Single Factor, Nested, Factorial, Split-Plot, Strip-Plot, Split-Split, Repeated Measures.
Modules are also built to accomodate some specialized features, such as sampling, replication and covariates.
A glossary is provided, as well as explanatory material each step of the way.
SAS is a trademark of SAS Institute, Inc, Cary, NC and is used to refer to their software. No endorsement is implied.
To send us comments or report errors
The project is supported by NIFA Hatch funding, the Tennessee Agricultural Experiment Station, the College of Agricultural Sciences and Natural Resources, the Department of Animal Science, and the Department of Plant Sciences at the University of Tennessee.
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DAWG authors: Arnold Saxton Bob Augé
Paperheads illustration above by Mike Reed