Day 30 Semester Project
Semester projects may deal with any topic that interests you [the student], as long as it is approved by the instructor.
Broadly, projects are expected to identify a research problem and develop a designed experiment that is appropriate for solving that problem. Projects consist of a manuscript and a tutorial that describes the research problem, the experiment design and the treatment design.
30.1 Learning objectives
- Be able to identify an experiment design that is appropriate for answering a given research question and discuss the strengths and weaknesses of that design for answering the question.
- Be able to write the materials and methods section of a paper/thesis, including the statistical model that corresponds the experiment design.
30.2 Partial deadlines
30.2.1 Project proposal - Due Friday June 20 at 2pm CT
Write a page-long project proposal that states your research problem and the objective of your project. An example of an appropriate project proposal can be found here.
30.2.2 Written report - Due Wednesday July 23 at 2pm CT for peer review
Submit a manuscript including:
- Introduction (background & justification of the problem)
- Methods, including:
- A complete ANOVA table describing the degrees of freedom associated to mean comparisons,
- A clear and complete description of the statistical model,
- R code that would be implemented to fit that model,
- Expected results
- Discussion of strengths and weaknesses of the experiment design (e.g., compare an RCBD with a split-plot design)
30.2.3 Oral presentation - Somewhere between July 21 - August 1
Prepare a 15 minute presentation of the core aspects of your project. Presentations should include at least:
- Motivation
- Methods, including a clear and complete description of the statistical model and code
- Discussion of strengths and weaknesses
30.2.4 Practical reads
- Casler, M.D. (2015), Fundamentals of Experimental Design: Guidelines for Designing Successful Experiments. Agronomy Journal, 107: 692-705. https://doi.org/10.2134/agronj2013.0114
- Casler, M.D. (2018). Power and Replication—Designing Powerful Experiments. In Applied Statistics in Agricultural, Biological, and Environmental Sciences (eds B. Glaz and K.M. Yeater). https://doi.org/10.2134/appliedstatistics.2015.0075.c4