Spatial Social Sciences Training Series LEVEL 1: FOUNDATIONS OF SPATIAL SOCIAL SCIENCES (BEGINNER)

Session 1 Exercise Workbook

Training Dataset

This is Lesson 2 Part 2

A beginner-friendly introduction to cartography for spatial social science. Learn how visual hierarchy, color theory, and good map design turn raw data into clear, meaningful, and accessible maps. Perfect for anyone learning to communicate insights through spatial visualization.

Part 3: Data Quality & Preparation
○ Common data quality issues in social datasets
○ Cleaning and validating spatial attributes
○ Practical Exercise: Cleaning a messy survey dataset

Part 3: Data Quality & Preparation
○ Common data quality issues in social datasets
○ Cleaning and validating spatial attributes
○ Practical Exercise: Cleaning a messy survey dataset

Geocoding Fundamentals (30 min)
○ Address matching and geocoding services
○ Coordinate systems and projections for social data

Hands-on: From Excel/CSV to Map (1 hour)
○ Importing tabular data into QGIS
○ Adding XY coordinates (lat/long conversion)
○ Geocoding addresses using MMQGIS plugin
○ Reverse geocoding techniques
○ Exercise: Geocode a household survey dataset

Joining Non-Spatial Data to Spatial Boundaries (30 min)
○ Table joins: demographic data to census tracts/wards
○ Spatial joins: attaching contextual information
○ Exercise: Join poverty data to administrative boundaries

📋 LEARNING OBJECTIVES
By the end of this session, you will be able to:
● [ ] Import CSV data with coordinates into QGIS as point features
● [ ] Understand coordinate systems and projections
● [ ] Geocode addresses using MMQGIS plugin
● [ ] Perform table joins to link demographic data to spatial boundaries
● [ ] Perform spatial joins to attach contextual information
● [ ] Export spatial data for future use

Cartographic Principles for Social Research (30 min)
○ Visual hierarchy and focus
○ Color theory: sequential, diverging, categorical schemes
○ Accessibility considerations (colorblind-friendly palettes)

Cartographic Principles for Social Research (30 min)
○ Visual hierarchy and focus
○ Color theory: sequential, diverging, categorical schemes
○ Accessibility considerations (colorblind-friendly palettes)

By the end of this session, you will:
1. Understand cartographic principles for social research
2. Create choropleth maps for continuous data
3. Use proportional symbols for count data
4. Choose appropriate color schemes
5. Create heat maps for density visualization
6. Design maps that communicate effectively

Part 1: Introduction to Spatial Distribution
What is spatial distribution?
Why it matters for social research
Overview of key measures

Part 2: Mean Center & Weighted Mean Center
Concepts and calculation
HANDS-ON: Calculate mean centers
Interpreting results

Part 3: Standard Distance & Dispersion
Measuring spatial spread
HANDS-ON: Calculate standard distance
Comparing distributions

Part 4: Directional Distribution
Detecting directional trends
Standard deviational ellipse
Social science applications

By the end of this session, you will:
- Calculate mean center (geographic average) of point distributions
- Measure standard distance (how spread out are points?)
- Analyze directional distributions (which way do things trend?)
- Understand when each measure is useful
- Interpret distribution statistics in social context