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Causal Inference Project Ideation

University of Minnesota via Coursera

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Overview

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Organizations can harness the power of causal inference through randomized field experiments, uncovering the true effects of interventions and enabling data-driven decision-making. In this course, we will delve into how companies are currently utilizing A/B testing. Additionally, we will explore the ethical considerations of conducting experiments and the econometric methods for analyzing causal relationships in observational data. Learning objectives: - Examine how companies are using field experiments for causal inference. - Analyze the ethical dimensions of field experiments. - Construct an issue tree for conducting randomized experiments about designing online referral bonus programs - Select a solution approach and define an experimental setup

Syllabus

Specialization and Course Overview
Module 1: Overview of Causal Inference

This module provides an overview of causal inference, starting with an introduction and lessons from real world examples. It then explores how companies use online A/B testing for personalization, key tenets and ethical considerations of controlled experiments, and concludes with methods for working with observational data, including the difference-in-difference method.

Module 2: Designing RFTs

This module covers the setup of Randomized Field Trials (RFTs), including hypothesis development, evaluation criteria, parameters, and treatment and control groups. It also addresses the importance of randomization, the selection of randomization units, and best practices for designing robust experiments.

Module 3: Causal Analytics Sprint Phase 1: Problem Identification

This module focuses on high-level needs identification, including understanding user journey maps, identifying business needs, and prioritizing them using PICK charts. It also covers SCQ analysis for referral bonuses in online word-of-mouth (WOM) and breaks down problems into subproblems, identifying common themes, and constructing an issue tree.

Module 4: Causal Analytics Sprint Phase 2: Solutions Mapping

This module covers results mapping by designing field experiments that align with the key questions that the business is interested in. It also delves into experiment design, focusing on hypothesis development and identifying control and treatment groups. The module concludes with a final project plan review.