Causal Inference Using Bayesian Structural Time-Series Models

 By Medium - 2021-03-20

Description

In this article I will provide you with a brief introduction to causal inference and why we would need it as a Data Scientist, and then I present a practical example of how to apply the concept using…

Summary

  • Investigating the effect of training activities on the volume of bugs reported by a software engineering team In this article I will provide you with a brief introduction to causal inference and why we would need it as a Data Scientist, and then I present a practical example of how to apply the concept using the Python library Causal Impact.
  • In our marketing example, we have a record of our sales after the intervention of a campaign, but we do not know what the sales would have been without that intervention.
  • However, to increase confidence in our conclusion we will utilize the Causal Impactlibrary for our statistical analysis.
  • The model will use the bug reporting data for all of the software engineering teams to help us determine whether the specified intervention was the true cause of the decrease in bugs reported for the Web team.

 

Topics

  1. Management (0.39)
  2. Backend (0.15)
  3. Frontend (0.13)

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