Final Report

Due: Dec 10 by 11:59pm

Weight: This assignment is worth 15% of your final grade.

Purpose: purpose

Assessment: Your submission will be assessed using the rubric at the bottom of this page.

Your final report should be a fully reproducible html webpage. It should include text, data, code, and plots. Your report should be written in a narrative format (i.e. using coherent paragraphs rather than a series of bullet points). You may use headings where appropriate to break up your report into sections. There is no length requirement - your report should be sufficiently detailed to address the requirements listed below and sufficiently concise such that it is expressed in the fewest necessary words. It is also perfectly acceptable for large portions of your final report to be identical to sections in your progress report, albeit all results should be “polished” and publication ready. Below is a list of specific items your report should include.

1. Get organized

  1. Download and unzip this template for your proposal report. Open the project.Rproj file and write your progress report in the report.qmd file. The template comes with some text and code explaining how to use it - you should delete the template code and text as it is only for explanatory purposes. Be sure to adjust the content in the YAML:

    • Write your project title in the title field (and provide a subtitle if you wish, or delete the subtitle field).
    • In the author field, list the names of all teammates, e.g. author: Luke Skywalker, Leia Organa, and Han Solo.
  2. Put the data you are working with for your project in the appropriate folders. Even if you are reading in data directly from a website (e.g. data <- read_csv("www.somewhere.com/data.csv)), be sure to download a local copy of the data and put it in the appropriate data folder.

  3. At the bottom of your report, add an Appendix section that includes data dictionaries for the key data sets used in your analysis as well as a copy of all of the code used in your report, which can be automatically generated with a single chunk like this:

```{r ref.label=knitr::all_labels()}
#| echo: true
#| eval: false
```

2. Introduction

Write an introduction section to describe the topic of your project to a general audience. Address a motivation for why the research question(s) you address in your project are interesting or important (why should the reader care about this?), and summarize key findings from your analyses.

3. State your research question

Clearly state your research question. You may want to write one more general question and then list several sub-questions that address more specific points. You should follow these guidelines.

4. Discuss your data sources

Discuss the data source(s) you are using for your analysis. For each data source:

  • Describe it and include urls or references to the original sources as well as links to any pre-processed or formatted data you are using. These are not always the same. For example, in the Mini Project 1 assignment, the original source was the Transit Costs Project whereas the data file used was posted on this GitHub repo.

  • Discuss details about how/when/where/why the data were collected. Do not make statements about whether you feel the data is “valid” but rather describe as much detail as you can about the data and let the readers make that assessment for themselves. Be sure to include:

    • Is the data you are using from the original source, or has it been pre-processed?
    • How was the original data collected and by whom?
    • Are there perhaps any missing data that might not have been observed?
    • Are there any potential biases in the data?
  • Finally, provide a data dictionary for each data file you are using in an appendix at the end of your report. The dictionary should contain a table of each variable name along with a brief description of the variable.

5. Describe your results with text and charts

  • Your analysis must include at least three polished charts / animations, though you can of course include more. Alternatively, you can build an interactive shiny app with at least two dynamic charts. If you build a shiny app, include a link to your app and screenshots of key charts from your app in your final report.
  • Display polished charts that either support or oppose your research question(s) or illustrate what else you might need to address your research question(s). It’s possible that your data / analyses only lead to another, more detailed question that you’re unable to fully address with the data you have - that’s okay! But we can still learn something along the way.
  • Your charts should be “polished” with appropriate labels / annotations and follow the design principles we have covered in class.
  • The chart types used should highlight the main point(s) you want to make or clearly show the relationship you want to emphasize. That is, make sure to use chart types that effectively communicate key insights.
  • Around your charts, write narrative text explaining what the chart shows and its significance towards addressing your research question(s). This should read as a continuous story rather than as a reply to each of the requirements described here.

6. Conclusions

Summarize in a paragraph or two your main findings from your analysis. What have we learned, and what else could we do next to go further on this topic? Are there other data sources that would really help extend your analyses?

7. Attribution

Include a short description of the specific contributions of each team member in your team. If all members contributed equally, you can just put the single sentence “All members contributed equally”. Team members who do not make meaningful contributions to their projects will not receive the same grade as that of their team mates.

8. Render and submit

Click the “Render” button to compile your .qmd file into a html web page. Then open the report.html file in a web browser and proofread your report.

Does all of the formatting look correct? Make sure there are no errors in the rendered file before submitting it.

Once you’ve proofread your report, create a zip file of all the files in your R project folder for this assignment and submit it on the corresponding assignment submission on Blackboard.

Only one person from your team should submit.

Grading Rubric

70 Total Points

Category Excellent Good Needs work
Organization & Formatting 5
All formatting guidelines are followed; YAML is correct with all team members listed.
4
Most formatting guidelines are followed; YAML is correct with all team members listed.
3 / 2
Several or all formatting guidelines not followed; YAML contains elements that aren't updated from the template.
Research Question 5
Research question is clear, focused, concise, complex, and arguable.
4
Research question is reasonably clear and focused, but may be too simple, too complex, or too verbose.
3 / 2
Research question is unclear and lacks focus; question is far too simple or overly complex.
Data Sources 5
Data sources are clearly described with valid urls or citations used; validity of and concerns about data are discussed; data dictionaries included in appendix.
4
Some data sources are not clearly described or urls / citations are missnig; validity of and concerns about data are minimally discussed; data dictionaries are in appendix.
3 / 2
Data sources are poorly described or missing; description of validity of and concerns about data are poor or missing; no data dictionaries provided.
Overall Analysis 18 - 20
Analysis and exploration of data conducted to address research questions; narrative text effectively used to describe analysis and results; overall analysis tells a coherent story addressing research question.
15 - 17
Analysis and exploration of data conducted mostly addresses research questions; text used to describe analysis and results, but writing quality is poor or not in a narrative format; overall analysis not fully coherent in addressing research question.
10 - 14
Analysis and exploration of data conducted does not address research questions; text poorly used or missing to describe analysis and results; overall analysis not coherent in addressing research question.
Visualizations 27 - 30
Charts expertly demonstrate best practices of visual design; charts are functionally accurate and address research questions; appropriate chart types used for conveying key messages; annotations are appropriate; minimum of 3 charts met.
22 - 26
Charts generally demonstrate best practices of visual design; some elements are distracting or confusing; some annotations missing, incomplete, or inaccurate; minimum of 3 charts not met.
15 - 21
Charts generally lack best practices of visual design; multiple confusing or unclear / distracting elements; unrelated to research question; minimum of 3 charts notmet.
Technical Things 5
All code runs without errors; all files included in the submitted .zip file; report is published on RPubs.
4
Code has only one or two error, otherwise runs; all files included in the submitted .zip file; or report is not published on RPubs
3 / 2
Code has multiple errors; submitted .zip file is missing components necessary to reproduce analysis; report not published on RPubs.