Exercise

Fabricated Bronze Age Cemetery

This is an exercise where you will load the data to R, do some cleaning, transformations and plotting!

The exercise simulates real-world archaeological research where you need to explore burial patterns, artefact distributions, and relationships between different aspects of the site…

The data set is an export from a fabricated database of an excavation of a Bronze Age cemetery.

Caution! The data set is purely synthetic and fabricated for didactic purposes.

Dataset Overview

The dataset consists of 3 related CSV files:

  • graves.csv – grave information and grave features, human remains information;
  • artefacts.csv – artefact records with materials, weights, preservation etc.

Brainstorming

Let’s formulate research questions to guide the analysis…

Tips for Success

  • Start simple: Begin with basic exploration before complex analysis.
  • Handle missing data: Archaeological datasets always have missing values – plan for them.
  • Document your findings: Add comments explaining what each analysis reveals.
  • Visualize early: Charts help identify patterns and outliers.

Download and explore the data…

  • Save the data as CSVs to your project folder.

.../data/burials.csv
.../data/artefacts.csv

  • Explore the CSVs.
  • Are there missing values?
  • How are missing values encoded?
  • Why are there missing values?

Load and explore the data

  • Load the data set to R.
  • Explore the structure of the data set.
  • How many graves and artefacts are there?
  • How many columns does each table have?
  • What is the structure?

Clean the data

  • Identify errors in encoding of the information etc.
  • Check lecture on Tidy data if needed.
  • What datatypes are there in each table?
  • What are the primary keys?
  • How do the tables relate one to the other?

Basic stats

  • Calculate descriptive statistics for numerical variables.

Questions to investigate

  • What is the average height of people buried in the cemetery?
  • What age categories are most common?
  • What is the mean and range of grave depths and mound diameters?
  • What is the average weight of bronze artefacts?
  • How many artefact types are represented?
  • What are the artefacts made of?

Data Visualizations

Create visual representations of your archaeological data.

Visualization tasks

  • Bar chart of artefact types.
  • Histogram of artefact weights by material.
  • Boxplot of estimated heights by sex.
  • Scatterplot of grave depth vs mound diameter.

Data Manipulation

Transform and combine your tables to answer further research questions.

Data manipulation tasks

  • Filter for well-preserved bronze weapons.
  • Create age groups from age categories.
  • Calculate artefact amount per grave.

Hint: Use left_join() to combine tables.
Hint: Use case_when() for complex conditional logic when creating new variables.

Grouped Analysis

Perform analyses grouped by categorical variables.

Grouped analysis tasks

  • Average artefact weight by type and material.
  • Number of artefacts per burial type.
  • How does height differ across sexes and age groups?
  • Preservation state distribution by artefact type.