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3 Applying Causal Inference

 

This chapter covers

  • Creating Directed Acyclic Graphs (DAGs)to describe how data was generated
  • Learn to explicit your assumptions with the DAG
  • Graphing recommender systems, pricing and marketing problems

Let’s look into some example situations where you can apply causal inference techniques, to get a feel for how the process works. Whenever you want to apply causal inference to a particular problem, there are two phases. An initial one where you need to translate the description of your problem into causal inference language. As we have already seen, graphs are an excellent tool for describing causal relationships and will help you to put together all the information you have about how data was generated, into a model. Creating the graph is a crucial part of applying causal inference because it will determine which formulas you should apply later on; for instance, if you need to apply the adjustment formula or not. Frequently, people get stuck at this stage and they don’t know where to start in creating the graph. For this reason, we will also use the examples in this chapter as an excuse for showing the process of graph creation, together with some tips that may help you get started on your own graphs.

3.1 In which steps of the causal inference analysis is the graph involved?

3.2 Steps to formulate your problem using graphs

3.2.1 List all your variables

3.2.2 Create your graph

3.2.3 State your assumptions

3.2.4 State your objectives

3.2.5 Check the positivity assumption

3.3 Other examples

3.3.1 Recommender Systems

3.3.2 Pricing

3.3.3 Simulations (optional section)

3.4 Chapter Quiz

3.5 Summary

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