13  Assessment 3

A project demonstrating data wrangling skills

13.1 Instructions

Your task is to replicate this html report using these datasets and code, and to generate an appropriate visualisation for the final plot. Nearly identical to assessment 2, the submission must contain the following:

In addition, your code should demonstrate the following skills:

You should include two short reflections on two things you did to improve your code clarity and efficiency and why they are important.

13.2 AI Declaration

It is School policy to include this specific AI declaration in any work that allows the use of generative AI. You can copy the code below and include it at the end of your assessment.

### Generative AI Declaration

Indicate [YES] or [NO] to all statements below to show how you have used generative AI tools in this assignment. You MUST declare all use of AI and take responsibility for the content of the assignment. We consider it a misuse of generative AI if you do not declare all uses, including initial exploration of the subject, literature searching, writing and editing, corrections for grammar and spelling, as well as any other tasks from the course.

* [YES/NO] Do you take full responsibility for the content of this submission, ensuring its adherence to academic integrity standards and compliance with University and subject-specific regulations regarding generative AI use as detailed in the assessment information sheet?

Did you use AI for:

* [YES/NO] General learning about a topic 
* [YES/NO] Idea generation or scoping of topic or research question
* [YES/NO] Searching and consulting the scientific literature
* [YES/NO] Summarising or explaining primary sources like journal articles
* [YES/NO] Planning the overall structure of a piece of work?
* [YES/NO] Translation of your own text from another language into English
* [YES/NO] Rephrasing your own text at sentence level
* [YES/NO] Language editing for spelling, grammar, clarity or tone
* [YES/NO] Referencing support, for example checking or producing citations, DOIs or formatting
* [YES/NO] Analysis support, for example statistical or qualitative analysis advice or interpreting output
* [YES/NO] Coding assistance, for example writing or debugging code
* [YES/NO] Visuals or media support, for example figures, diagrams, slide layout or transcription of my own * recordings
* [YES/NO] Something else (explain under **Sources of Learning**)
* [YES/NO] Avoided use of AI tools in any way to assist with this assignment or my learning of the topic

13.3 Hints and Tips

  • The html theme used by the demo report is flatly
  • The ggplot theme is theme_bw()
  • You will not be asked to do anything ‘tricky’ in this assessment, so if you find yourself needing 20 lines of code just to customise the labels in a plot, try looking for more efficient alternatives.
  • You will definitely need to join data, and convert between wide and long. Make sure you do this efficiently, creating the minimum number of extra data tables needed, and not re-creating the same table for different tasks.
  • If you find yourself doing the same thing to many columns, you could probably do it more efficiently by reshaping the data longer first
  • Use pipes to avoid creating many single-use tables.
  • The figure width and height of Figure 1 are 10 and 5 (it is fine to change this if your fonts are a slightly different size)

13.4 Submission

  • Covers: chapters 1-7, emphasising 5-7
  • Worth: 30%
  • Do not put your name in your report; use your student ID as the author.
  • Please submit a zip file containing:
    1. the .rproj file
    2. your reproducible script, named report3_studentID.qmd
    3. any additional files necessary to reproduce your report(e.g., images or bibliography files),
    4. the rendered html report, named report3_studentID.html.

13.5 Marking Rubric

ILO A: Excellent B: Very Good C: Good D: Satisfactory E: Poor
Research & Knowledge
Skills from Chapters 1-3: You demonstrate skills to create reproducible reports and visualise data
Data Import and Joining: You import and join together data clearly and correctly
Data Reshaping: You can reshape data between long and wide formats where approriate
Data Wrangling: You demonstrate the ability to select and filter data, create new data columns, and edit existing data columns
Evaluation
Original Plot: The original plot is appropriate to the question asked
Reflection: Your reflections note valid areas where code clarity and efficiency are important, and correctly identify and explain techniques you used to ensure them
Communication
Code Clarity: Your code is organised in the quarto script cleanly and clearly, using separate code chunks to intersperse text and relevant code. Your code chunks contain comments that clarify the purpose of the code, but not overly-explaining each step. The names you use for objects are clear, consistent, and concise.
Code Efficiency: While there are many ways to do the same things in R, some ways are more efficient than others. These avoid unnecessary code (e.g., do not load packages you do not use) and redundancy (e.g., do not load or process the data the same way in several places).