Lab report module 6

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

We are investigating radiocarbon age data from a selection of famous Egyptian pyramids. What does this data tell us about when the pyramids were built?

Here's what you need to do:

1. Create a new RStudio project (New Project -> New Directory -> New Project), and
   • save it as archy-208-module-6-bmarwick (replace my UW ID with yours), you will get a new, empty folder, ready to work in
2. Download the CSV file with the data here, Download CSV file with the data here, this is from Bonani et al 2001 Links to an external site., which is our target article for this week that you should read to ensure you understand the topic of this lab. 
   • use your desktop folders to move this data file into your RStudio project directory that you just created.
   • File names are vital here: do not rename the CSV file. We can't grade your assignment if the file names are not exactly as specified here (check for numbers magically appearing at the end of the filename, that means you've downloaded it multiple times, you should delete the other copies). 
3. In your new project, create a new Quarto file (File -> New file -> Quarto Document -> click "Create"), and:
   • save your qmd file as archy-208-module-6-bmarwick.qmd (replace my UW ID with yours),
   • delete all the template content
   • Ensure your 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
     • the output format set as html, hint: format: html: self-contained: true
     • warnings and messages suppressed in the output, hint: execute: warning: false
     • increase the image quality of the plots, hint: fig-dpi: 600
     • customize the date label, hint: title-block-published: "Last updated"
4. In your qmd file, use these headings, and write a total 8-12 fully-formed sentences containing specific details and concrete nouns that answers these questions:

• • Introduction: What is the aim of your report? See Thursday's lecture slides Download Thursday's lecture slides for the specific aims to mention here (1-2 sentences containing specific details and concrete nouns).
  • Data: What type of data are you analyzing and where does it come from? (2-3 sentences containing specific details and concrete nouns)
    • use at least one example of inline R code to get a meaningful summary value (do not hard-code any values, e.g. 'two')
    • ensure you have a code block that cleans your data,
    • your code must use pipes
    • your code must use the mutate function
    • your code must use the select function
    • your code must use the arrange function
    • your text must cite the publication that originally presented the data in APA style (how? do not include the title of the article in your sentence), and include it in your reference section.
  • Exploratory data visualisation: What do you observe when you visualise the data? (3-4 sentences containing specific details and concrete nouns)
    • you need to write R code that produces a panel plot showing your calibration of the ages (one plot per age)
    • you need to write R code that produces one plot with all ages on the same time axis
    • you need to write R code that produces one SPD plot to identify the peak time of pyramid building
    • you need a caption and cross-reference for each figure or panel of figures
    • Each visualisation needs at least one complete sentence describing your observations.
  • Conclusion: According to your data analysis, what is your conclusion about when the pyramids were built? (2-3 sentences containing specific details and concrete nouns) 
    • you need a statement that answers the questions presented in the lecture, using key words and phrases presented in the lecture, and cross-references one of your plots. When you write your main claim here, you must state how that claim is supported by your data analysis in the above section. 

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

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

6. Upload to Canvas your two files (please do not zip them):

• • your qmd file, correctly named, with correct YAML, with code and text, and
  • your HTML file, containing the output of your code and text, with no warnings or messages from the code visible

If you get stuck at any point here please let us know at any time by posting a message to our Discord workspace. We want you to succeed!

Additional resources: 

• Analysing radiocarbon dates using the rcarbon package Links to an external site.
• Simple plotting options for radiocarbon dates Links to an external site.
• Using Bayesian radiocarbon chronology package Bchron Links to an external site.