Exercise

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.