STAT 5303: Designing Experiments
Spring Semester 2017
Under Construction---come back to this page later to check for updates.
Official University policies on many issues are available
Some good news and some bad news:
The bad news is that the textbook is out of print so it is not readily available from bookstores, although you may find a used copy somewhere.
The good news is that the author (Prof. Oehlert) has generously made the book available as a no-cost download. Go to
for links to the PDF file for the book itself and datafiles for examples and exercises from that book.
You can also buy a hard copy version of that PDF file from Paradigm Copies.
Basic R information
We will use R.
Here is an introduction to R.
You may download R for Macintosh, Windows, and Linux from the
R package Stat5303
We will use Prof. Oehlert's R package called Stat5303, which
adds some extra commands that we will need.
The current version of this package is here.
You will need to download and install two packages, but they will require several other packages, too, so it may take a while. Fortunately, you only need to do that once.
Then each time you start R you will need to use
to make the extra commands available in that R session.
This is as much a list of what the project is not as it is a list of what it is.
- There is more information in the text---see chapter 20.
- The project involves a designed experiment, not an observational study or a survey.
- You need to clearly identify experimental units and treatments and, if appropriate, blocking factors and measurement units.
- Describe how you use randomization in your experiment.
- You should analyze the data using methods we have covered in this course, such as ANOVA for a continuous response.
- Remember that we've studied comparative experiments, so you probably want to examine differences between treatments.
- No human subjects, nor anything else that would require review board approval.
- You need to propose a question, plan an experiment to answer that question, perform that experiment, collect and analyze the data, and write a final report covering all of that.
- Remember to include in both the proposal and the final report enough background information so someone who is not trained in your area of expertise can understand what you're trying to do and why someone would want to do it.
- This has to be a new experiment; you cannot just take some old data from work you did before and reanalyze that.
- This is to be an actual experiment, and not just a computer simulation.
- The proposal is not like a contract, but it needs to be specific enough so I can tell tell if what you're planning fits within these guidelines.
Comments? Questions? Send me an e-mail note:
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