Social Data Analysis

Overview

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Short description

Thanks to "Social Data Analysis" a person will engage with advanced techniques to analyze data and to distinguish a causality link from a simple correlation. We will do it by looking both at the theoretical side and at the most recent application.

Being able to identify causality links represents a crucial skill for a person interested in understanding the data that today's world produces.

The CPD Social Data Analysis teaches students how to apply quantitative methods to conduct causal impact analysis using data. In particular, students will learn how econometric methods can be used to answer questions related to human behaviour and strategic decision-making with the help of regression based econometric methods.

The module has an applied focus, demonstrating the use of econometric methods used for impact evaluation with practical applications and referring to examples from recent studies that apply those methods to answer key questions in the social sciences.

On successful completion of this module students will be able to:

• determine which methods can be used to analyse different datasets for addressing different questions of relevance to the social sciences.
• critically assess findings of studies that apply these methods.
• design their own randomized experiments.
• conduct their own causal regression analysis using the statistical software package R.

On successful completion of the CPD, students will receive a Certificate of Completion.

What topics will you cover?

The CPD focuses on applied causal regression analysis providing an understanding of econometric methods for use with big data. In particular, the course covers regression-based evaluation methods to assess the casual relationships between different factors at play.

These include the use of panel data, difference-in-differences estimation, matching and regression discontinuity designs, randomized experiments, and natural or quasi-experiments.

The CPD has an applied focus, demonstrating the use of these methods with practical applications using the statistical software package R and referring to examples from recent studies that apply those methods to answer key questions in the social sciences. 

Who is this course for?

The target learner cohort are participants working in the private sector, for example ITC, finance, banking sectors. Participants are expected to have basic computer skills and some quantitative experience through prior training in statistics e.g. degree or equivalent experience, or having taken the Trinity CPD An Statistics and Regression Analysis’. Participants should also have access to a laptop with camera and a microphone.

Who teaches the course?

Assistant Professor Nicola Fontana, Department of Economics, School of Social Sciences and Philosophy, Trinity College Dublin.

How is the course delivered?

1. The CPD will be delivered over 7 weeks (including one break week). The course will be fully online with the following structure per week:
   1. 1h 30m: Introduction to the topic – recorded video
   2. 1h live online lecture
   3. 30m: applications in R (the software) – recorded video
   4. 1 hour self-study (exercises)

Additionally, participants are expected to undertake 20 hours of self-study over the course of the programme to review the material provided. Students will give presentations during the last week of the module. In order to be awarded the Certificate of Completion in Social Data Analysis, participants will need to have delivered the final presentation.