Urban Data Analytics

Urban Data Analytics 1

Course introduction

For the first time in history, more than half of the world’s population lives in urban areas. This does not only mean that a majority of people worldwide reside in cities, but also that cities are increasingly becoming larger and more complex. To account for that complexity, quantitative and qualitative data analysis are useful tools to approach a wide range of research questions that concern cities. 

In the first module, participants learn about quantitative data analysis. An ever-increasing number of quantitative data sources that cover urban areas and cities on different scales have become available, requiring urban managers to have the knowledge and skills for analysing such data and making sense out of them. The first module of this course will teach students how to harness the power of quantitative urban data by mastering the way they are prepared, visualised, and analysed. 

In the second module, participants learn about qualitative data collection and analysis. They will learn how to approach qualitative methods and how to analyse data. Collecting and making sense of in-depth qualitative data on complex urban issues is crucial for urban managers to understand and respond to how urban complexity is constructed, maintained, experienced, and contested.

Course objectives

The aim of this course is to equip participants with a basic tool set that will enable them to conduct quantitative and qualitative data analyses. More specifically, after following UDA participants will have achieved the following learning objectives:

Both Modules

• Understand what quantitative and qualitative data analysis entail and how they differ from each other.
• Identify situations in which quantitative and/or qualitative data analysis provide useful information in an urban context.
• Examine how findings can be translated into policy recommendations and/or reflection on theory.

Module 1

• Employ the main tools of descriptive data analysis and visualization. 
• Explain how random sampling is used for hypothesis testing. 
• Conduct regression analysis using the ordinary-least-squares method. 
• Apply the knowledge in practice using statistical software. 
• Interpret quantitative data output. 
• Evaluate the findings for policy implications and policy recommendations. 

Course content

The course introduces participants to basic data analytics and entails the following seven sessions:

1. Introduction to quantitative data analysis
2. Descriptive statistics (measures of central tendency, measures of spread, correlation)
3. Data visualisation
4. Probability and estimation
5. Hypothesis testing
6. Simple regression analysis
7. Multiple regression analysis

The statistical software that will be used in this course is STATA 16.

Course information

Urban Data Analytics 2

Course introduction

For the first time in history, more than half of the world’s population lives in urban areas. This does not only mean that a majority of people worldwide live in cities, but also that cities are increasingly becoming larger and more complex. In this context, collecting and making sense of in-depth qualitative data on complex urban issues is crucial for urban managers to understand and respond to how urban complexity is constructed, maintained, experienced and contested.

Course objectives

The objective of the course is to help students gain methodological skills to design and conduct qualitative research.  At the end of the course, the students will be able to

At the end of the course, the students will be able to 

• Understand theoretical and practical aspects of conducting qualitative urban research.
• Apply methodological skills on building qualitative research design, data collection and analysis of qualitative data.
• Critically reflect on qualitative research findings.
• Apply ethical concerns, as well as concerns for validity and reliability in qualitative research.

Course content

Urban Data Analytics (UDA) Qualitative course introduces urban qualitative research and focuses on qualitative data collection and analysis. Covering both theoretical and practical dimensions of conducting qualitative research, it helps the students to gain methodological skills to design and conduct qualitative research in urban settings. The course is structured around the following themes:

1. Introduction to Qualitative Urban Research (Qualitative vs. Quantitative Research, Sampling);
2. Qualitative Data Collection Tools (Interviews, Focus Groups, Observations, Online and Offline Qualitative Data Collection);
3. Qualitative Data Analysis (Types, Data Preparation and Coding, Presentation of Findings, Using Atlas TI).

Together with UDA Quantitative and Research Design courses, this course provides students a practical guide for the design and implementation of their thesis research. 

Course information