| 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 Several or all formatting guidelines not followed; YAML contains elements that aren't updated from the template. |
| Research Question | 10 / 9 Research question is clear, focused, concise, complex, and arguable. |
8 / 7 / 6 Research question is reasonably clear and focused, but may be too simple, too complex, or too verbose. |
5 / 4 / 3 Research question is unclear and lacks focus; question is far too simple or overly complex. |
| Data Sources | 10 / 9 Data sources or plausible data sources are clearly described; validity of and concerns about data are discussed. |
8 / 7 / 6 Identified data sources or plausible data sources are not clearly described; validity of and concerns about data are minimally discussed. |
5 / 4 / 3 Data sources are poorly described or missing; description of validity of and concerns about data are poor or missing. |
| Evaluation of Expectations | 10 / 9 Clear discussion of whether or not proposal expectations about variables and relationships were met; evidence from data provided to support discussion. |
8 / 7 / 6 Description of only one expected variable, relationship, or chart, or minimal description of two; minimal evidence from data provided to support discussion. |
5 / 4 / 3 Poor or missing description of variables, relationships, or charts; poor or missing evidence to support discussion. |
| Data Visualization 1 | 10 / 9 Chart clearly communicates key message; Chart is an appropriate choice for showing the relationship / comparison; Design elements are clear and not confusing / misleading; Chart is functionally accurate and generally easy to understand; Annotations (if used) are appropriate; Chart addresses the research question posed. |
8 / 7 / 6 Chart communicates key message; Chart is generally appropriate for showing the relationship / comparison; Some design elements are distracting or confusing / misleading; Chart is functionally accurate; Annotations (if used) are appropriate; Chart mildly addresses research question. |
5 / 4 / 3 Key message of chart is unclear; Chart is inappropriate for showing the relationship / comparison; Design elements are distracting or confusing / misleading; Chart is functionally inaccurate; Annotations are not used; Chart is unrelated to research question. |
| Data Visualization 2 | 10 / 9 Chart clearly communicates key message; Chart is an appropriate choice for showing the relationship / comparison; Design elements are clear and not confusing / misleading; Chart is functionally accurate and generally easy to understand; Annotations (if used) are appropriate; Chart addresses the research question posed. |
8 / 7 / 6 Chart communicates key message; Chart is generally appropriate for showing the relationship / comparison; Some design elements are distracting or confusing / misleading; Chart is functionally accurate; Annotations (if used) are appropriate; Chart mildly addresses research question. |
5 / 4 / 3 Key message of chart is unclear; Chart is inappropriate for showing the relationship / comparison; Design elements are distracting or confusing / misleading; Chart is functionally inaccurate; Annotations are not used; Chart is unrelated to research question. |
| Technical things | 5 All code runs without errors; all files included in the submitted .zip file. |
4 Code has only one or two error, otherwise runs; all files included in the submitted .zip file. |
3 Code has multiple errors; submitted .zip file is missing components necessary to reproduce analysis. |
Progress Report
Due: Oct 29 by 11:59pm
Weight: This assignment is worth 6% of your final grade.
Purpose: purpose
Assessment: Your submission will be assessed using the rubric at the bottom of this page.
Write a report summarizing progress you have made towards your project thus far, including summary statistics of your data and preliminary charts. You should have already identified data source(s) for your project and begun exploring the data. 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. Below is a list of specific items your progress report should include.
1. Get organized
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 - should should delete this code as it is only for explanatory purposes. Be sure to adjust the content in the YAML:
- Write your project title in the
titlefield (and provide a subtitle if you wish, or delete thesubtitlefield). - In the
authorfield, list the names of all teammates, e.g.author: Luke Skywalker, Leia Organa, and Han Solo.
You should also put the data you are working with for your project in the appropriate folders.
2. Write your research question
This can (and almost certainly should) be a revised research question from your proposal.
Again, follow these guidelines.
3. 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, for Mini Project 2, the original source was the Transit Costs Project whereas the data file used was posted on this GitHub repo.
Discuss the validity of your data:
- 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?
- Could the data be biased in some way?
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.
4. Evaluate your proposal expectations
- Do you find support for your original proposal expectation about how one variable might be distributed? Show it by looking at summaries of the variable. If that variable doesn’t exist in your data, discuss another key variable instead and how it is distributed.
- Do you find support for the expected relationships you wrote about in your proposal? If those variables don’t exist in your data, discuss one key relationship that you have identified between two or more variables.
5. Include at least two preliminary charts
- Your charts should either support or oppose your research question(s), or they should illustrate what else you might need to address your research question.
- The preliminary charts must be different in nature. For example, it would not be appropriate to make two bar charts that are otherwise the same except for having a different y axis.
- You may choose whatever chart types you wish, but your choices should highlight the point you want to make or should clearly show the relationship you want to emphasize. Consider these resources when choosing your charts.
- Your charts cannot be simple counts summarizing just one variable in your data. You should specify what relationship you are looking for in your charts and whether or not you see evidence of that relationship.
- Your charts should follow the design principles we have covered in class. They do not have to be fully “polished” yet, but at a minimum they should be accurate (i.e. not misleading) and they should not include distracting non-data ink.
6. 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. If you are having any issues or disputes among team members, please contact Professor Helveston ASAP so we can find a resolution.
7. 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.