Lab report module 3

The purpose of this assignment is for you to demonstrate basic familiarity with importing, inspecting, cleaning, visualising, and interpreting archaeological data.

We are investigating palaeobotanical data from archaeological landscapes in Bolivia. What kinds of plants characterised the ancient gardens on this landscape, and how do the two sample areas compare?

Here's what you need to do:

1. Create a new RStudio project (New Project -> New Directory -> New Project), and
   • call it archy-208-module-3-bmarwick (replace my UW ID with yours).
   • You should get a new, empty project folder, ready to work in
   • Download the CSV file with the data here and move it into your RStudio project directory that you just created. The data are from a study by Boixaderaa et al 2019 Links to an external site..
   • File names are vital here, it must keep its original name: do not rename the data file. Do not download it multiple times because this can cause confusion, and may cause you to lose points when your assignment is graded.
2. In your new project, create a new Quarto file (File -> New file -> Quarto Document -> click "Create"), and:
   • save it as archy-208-module-3-bmarwick.qmd (replace my UW ID with yours),
   • delete all the template content
   • Ensure the YAML front matter has:
   • an effective title (how?), e.g. in the form of a question or statement
   • your name, hint: author: "Ben Marwick"
   • the date automatically inserted, hint: date: now
   • html set as the output format, hint: format: html: self-contained: true
3. In your new qmd file, use the following headings, and write a total of 4-5 fully-formed sentences that answer these questions:

• • Introduction What is the aim of your report? (See Thursday's lecture slides Download Thursday's lecture slides)
  • Data What types of data are you analysing and where does it come from?
    • use one example of inline R code to get a summary value (do not write in any hard-coded values)
    • ensure you have an R code block that cleans your data, uses pipes, and the mutate function
    • cite the publication that originally presented the data in APA style, and include it in your reference section.
  • Exploratory data visualisation What differences and similarities do you observe for the two sampling locations when you visualise the data?
    • ensure you have an R code block that produces at least one visualisation using the ggplot() function
  • Conclusion What is your conclusion about the kinds of plants used in these gardens, and how do the two sample areas compare?
    • Check the lecture slides for the specific questions to answer in your conclusion.
    • Search google for the common names of the plants, and use these in your conclusion. 

4. Render your qmd file to output a HTML document.

• Check that in your qmd file your CSV file name is exactly the same as ours.

5. Before the next lab class, upload to Canvas your three files, one at a time (please do not zip them into one file), and only upload each file once:

• your data file, correctly named, check that your data file name is exactly the same as ours
• your qmd file, correctly named, with correct YAML, with code and text, and
• your HTML file, containing the output of your code and text

If you get stuck please let us know at any time by posting a message to our Discord workspace.  

Additional resources: 

• Software Carpentry: Data types in R Links to an external site. 
• Introduction to Data Science: String processing Links to an external site. 
• R for Data Science: Working with strings Links to an external site. 
• Data Carpentry: Data visualization with ggplot2 Links to an external site. 
• R for Data Science: Data visualisation Links to an external site.