2023-09-21T12:02:51+05:30
Last semester: Diving into the World of Causal Inference and Virtual Machines
During the previous semester at Tilburg Science Hub, we were involved in a time of learning, exploring, and innovating. We've been busy with developing new content and using new tools that we're excited to share with you.
We have mainly been busy creating new content in the field of causal inference and also delved into the world of virtual machines. Let's take a closer look at the resources we've created in these two areas.
Causal Inference
Causal inference has been the most important subject of our exploration. We have put together a comprehensive set of tools to guide you through this complex but captivating subject:
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Introduction to Instrumental Variables Estimation: We start with a thorough introduction to IV (Instrumental Variable) estimation, which is a fundamental concept in the field of causal inference.
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Doing Calculations with Regression Coefficients Using deltaMethod: We show you how to handle regression coefficients with precision through the deltaMethod.
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Impact evaluation: We take a closer look at impact evaluation through regressions, uncovering how interventions and policies can be rigorously analyzed to make informed decisions.
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Synthetic Controls: Discover the power of the Synthetic Control Method, which is an invaluable tool for causal inference in diverse research scenarios.
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Fixed-Effects Estimation in R with the fixest Package: Lastly, we dive into fixed-effects estimation using the `fixest`` package in R, which is particularly useful for panel data analyses (and, super super fast!).
Virtual Machines
Besides our focus on causal inference, we've also explored virtual machines (VMs). Think of them like a supercomputer that you can rent on-demand. We've created some building blocks related to virtual machines to help you set them up and run environments in the cloud.
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Configure a VM with GPUs in Google Cloud: Learn how to use the computing power of GPUs on Google Cloud by setting up a customized VM to meet your research requirements.
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Import and run a Python environment on Google cloud with Docker: Explore the world of containerization and Docker to import and run Python environments on Google Cloud, enhancing the reproducibility and efficiency of your work.
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Export a Python environment with Docker and share it through Docker Hub: Learn to export Python environments with Docker and streamline collaboration by sharing them on Docker Hub, ensuring easy access for fellow researchers.
Enhancing Your Research Skills in Causal Inference and Virtual Machines
Our aim is to support your exploration of causal inference and virtual machines. These resources are designed to equip you with the knowledge and tools needed to excel in your research.
Curious about what we will be working on next semester? Keep an eye on our blog!