Final Project Paper. Instructions, Template & Rubric

SNR 690. Contemporary Approaches to Quantitative Methods

1 Overview

Your final paper is the main deliverable of this course. It brings together everything we have worked on this semester: from the Method-Question-Data Triangle (Week 3), to method justification and assumption checking (Weeks 5–9), to your own research question and data.

The paper should be written as a submission to a journal of your choosing. You must identify a target journal before you begin writing, review that journal’s author guidelines (formatting, citation style, structure expectations), and follow them. Your paper must demonstrate that you can align a research question with appropriate quantitative methods, carry out the analysis, and communicate the results clearly and honestly.

You need to include the journal that you are tageting in your submission.

Due Date

Your final paper is due May 10, 2026.

Submit your paper by either submitting it via Canvas or by pushing the final version to your GitHub repository. Make sure the repository is shared with me (see Step 4 in the Project Home page).

2 What to Submit

A written paper. The paper can be a .qmd, .Rmd, .docx, or .pdf file but remember that you need to read your target journal’s author guidelines to ensure your submission meets their requirements.
All code pushed to your GitHub repository, or a supplementary material. The code must be organized and commented so that someone else could run it and reproduce your analysis.
A README ONLY IN CERTAIN CASES. Please read. Put this file in your repository and it should include your research question, variables, analysis method, assumption check table, and expected timeline, but only if you have not already included this information in your paper. If your paper already includes all of this information, you do not need a README.

3 Paper Structure and Requirements

Your paper must be structured with at least the following major sections. You should follow the specific formatting and section conventions of your target journal, but the content below is required regardless of journal style.

3.1 1. Introduction

State your research question, research objective or BOTH explicitly.
Provide enough background for the reader to understand why the question matters. But this is not the main focus of the paper, so be concise. You can assume your reader has a general background in natural resources, plant sciences, etc., but not necessarily in your specific topic.
I encourage a focused introduction rather than a long one.
End the introduction with a clear statement of your objective and/or hypothesis.

3.2 2. Methods

This is one of the two most important sections of your paper. I expect substantial detail here.

Your Methods section must include:

Study design or data structure: Describe your experimental design, sampling scheme, or observational data structure. Identify your response variable(s), predictor variable(s), and any grouping or nesting factors.
Analysis method(s): Describe the statistical method(s) you used and justify your choice. Reference the Method-Question-Data Triangle: explain why this method fits your question and data, why a simpler method would be insufficient, and why a more complex method is not warranted.
Model specification: Write out your model (e.g., the lmer() or glm() call, or the mathematical equation). Be specific about fixed effects, random effects, distributions, and link functions as applicable.
Software and packages: State the software and R packages you used, with version numbers.

3.2.1 Assumptions and Assumption Checks

This subsection can be included in the Methods section or the README. But you need to share it. You must:

List every assumption your chosen model requires (e.g., independence of residuals, normality of random effects, homoscedasticity, no spatial autocorrelation, etc.).
Describe how you evaluated each assumption (e.g., residual plots, Shapiro-Wilk test, variogram, etc.).
Report what you found and what you did if an assumption was violated (e.g., transformed variables, switched to a different model, acknowledged the limitation).
Use the assumption check table format we have used in class:

Assumption	How checked	Result	Action taken
(e.g., independence of residuals)	(e.g., residual vs. fitted plot)	(e.g., no pattern observed)	(e.g., none needed)
(e.g., normality of random effects)	(e.g., QQ-plot of random effects)	(e.g., slight departure)	(e.g., acknowledged in Discussion)

Remember

The goal is not to have all assumptions perfectly met. Red-flag assumptions are honest limitations that belong in your Discussion section. Every study has them. What I am looking for is that you identified them, checked them, and dealt with them transparently.

3.3 3. Results

This is the other most important section. Your Results section must include:

Plots and figures: Include at least one figure that displays your data and/or model results. Figures should be clear, well-labeled, and interpretable without reading the text. Follow your target journal’s figure formatting guidelines.
Model output: Present your key results (coefficients, confidence intervals, p-values, effect sizes, or posterior summaries or whatever is appropriate for your method and inferential framework).
Interpretation: Describe what the results mean in the context of your research question.
Tables: If appropriate, include summary tables of model results, means, or comparisons.

3.4 4. Discussion

Summarize your main findings and how they answer your research question.
Discuss the alignment between your research question, methods, and results. Did your analysis answer the question you set out to address?
Discuss limitations honestly, including any assumptions that were violated or could not be fully checked.
Connect your findings to the broader literature or practical implications in your field.
If relevant, suggest next steps or future analyses.

3.5 5. References

Use the citation style required by your target journal.
Cite all sources, R packages, and methods references appropriately.

4 Rubric

Your final paper is worth 25% of your course grade (as part of the Final Project component, which includes both the paper and the presentation). I will evaluate your paper using the following criteria:

Criterion	Excellent (A)	Good (B)	Needs Improvement (C or below)	Weight
Research Question & Alignment	Research question is clearly stated. Methods, results, and conclusions are logically aligned with the question. The Method-Question-Data Triangle is clearly satisfied.	Research question is present but could be sharper. Alignment is mostly clear but has minor gaps.	Research question is vague or missing. Methods do not clearly connect to the question asked.	15%
Methods. Correctness & Clarity	Statistical method is appropriate for the data structure and question. Model is fully specified (equation or code). Justification is clear and references course concepts (e.g., why not simpler, why not more complex).	Method is reasonable but justification is thin or model specification is incomplete.	Method is inappropriate for the data, or no justification is provided.	25%
Assumptions & Assumption Checks	All relevant assumptions are listed. Each is checked with an appropriate diagnostic. Results and actions are reported transparently. Violated assumptions are acknowledged honestly.	Most assumptions are listed and checked, but some are missing or checks are superficial.	Assumptions are not discussed, or the section is missing entirely.	15%
Results. Plots, Figures & Interpretation	Results are presented clearly with well-formatted figures and tables. Output is interpreted in context, not just pasted. Figures are publication-quality and follow journal guidelines.	Results are present but figures need improvement, or interpretation is too brief.	Results are missing, unclear, or consist of uninterpreted R output.	20%
Writing, Organization & Journal Compliance	Paper is well-organized, follows the target journal’s author guidelines (citation style, formatting, structure). Writing is clear and concise. Instructor voice is absent (i.e., it reads like a real paper).	Organization is reasonable but does not closely follow journal guidelines, or writing has some unclear passages.	Paper is disorganized, does not follow any journal format, or has significant writing issues.	15%
Reproducibility & Code	Code is available in the GitHub repository. Analysis can be reproduced by running the code. Software and package versions are reported.	Code is present but incomplete or not fully reproducible.	No code is shared, or code does not run.	10%

5 Timeline Reminders

Date	Milestone
April 28, 30, or May 5	Final presentation (see Final Presentation Instructions)
May 10, 2026	Final paper due

Your presentation date is not the same as your paper due date.

Return to Project Home · See also: Final Presentation Instructions