Collect a research-type data set and analyze the data using methods that are covered in our Experimental Design course. You may use any of the experimental designs we discuss in class except completely randomized designs from Chapter 2. Your project is due in two parts. The first three sections of the project are due (via email or hardcopy) by Monday, October 2, while the final posters will be displayed during dead week. Posters must have an adequate font size (at least 18 for text, and larger for headings and the title). Posters with font sizes that are too small will receive a lower grade. Your poster should address the following issues:

- The context of the experiment
- General information about the topic.
- The general hypothesis of interest.
- Specify H0 and H1 for the tests of major interest.
- The goals of the experiment, i.e., what it would contribute to knowledge in the field. Also, relate it to other experiments already done in the field.

- Define the experimental design.
- State the design used, and describe the experiment in enough detail to identify the design.
- Defend the choice of the blocking variable(s) and the levels used in your experiment. If you don't use a blocking variable, defend why not.
- Define the treatment factor(s), whether they are fixed or random, and the levels. Defend why they are used in your experiment.
- Describe the dependent variable, and specify any potential problems one might encounter in measuring this dependent variable.
- When applicable, use power calculations to calculate the sample size needed to detect differences that you believe are of practical significance. Show your work for the calculations.

- Describe the population from which the subjects will be
selected. Describe the sampling procedure and the random
allocation of subjects to treatments.

These first three sections (listed above) are due on lecture Monday, October 2.

- Describe the analysis of variance.
- Write out the Linear Model using notation like what is used in the text (not just computer code).
- Lay out the appropriate ANOVA Table through the expected mean squares.
- Discuss any uses of post hoc comparisons that may be appropriate to your experiment.
- Analyze the data. Conduct exploratory analyses and generate some graphs or plots to describe the data. Present the main results from the analyses .

- Discuss the implications of your results for this field, and compare your results to other published results. (Most of this should follow from your results and the background information in part 1)

Special thanks to Dr. Bill Mickelson, whose Stat 401 Project Description I have borrowed and adapted to make this Project Description.

Note: the rubric I use to grade the posters uses the following categories: Was the motivation for the research clear? Was the process of data collection clear? Was the choice of experimental design clear? Was the choice of experimental design appropriate? Was the data analysis explained clearly? Was the data analysis appropriate (Including graphs)? Were assumptions checked? Quality of overall presentation and effectiveness of communication?