Description

Book Synopsis

When you know the cause of an event, you can affect its outcome. This accessible introduction to causal inference shows you how to determine causality and estimate effects using statistics and machine learning.

In Causal Inference for Data Science you will learn how to:

  • Model reality using causal graphs
  • Estimate causal effects using statistical and machine learning techniques
  • Determine when to use A/B tests, causal inference, and machine learning
  • Explain and assess objectives, assumptions, risks, and limitations
  • Determine if you have enough variables for your analysis


It''s possible to predict events without knowing what causes them. Understanding causality allows you both to make data-driven predictions and also intervene to affect the outcomes. Causal Inference for Data Science shows you how to build data science tools that can identify the root cause of trends and events. You''ll learn how to interpret historical data, understand customer behaviors, and empower management to apply optimal decisions.

Causal Inference for Data Science

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    A Hardback by David Sweet

    £43.69

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    RRP £45.99 – you save £2.30 (5%)

    Order before 4pm today for delivery by Fri 11 Sep 2026.

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      Book details

      Publisher Manning Publications
      Published 1/28/2025
      ISBN-13 9781633439658
      978-1633439658
      ISBN-10 1633439658
      Also in:
      Dictionaries, Reference & Language Data science and analysis

      Description

      Book Synopsis

      When you know the cause of an event, you can affect its outcome. This accessible introduction to causal inference shows you how to determine causality and estimate effects using statistics and machine learning.

      In Causal Inference for Data Science you will learn how to:

      • Model reality using causal graphs
      • Estimate causal effects using statistical and machine learning techniques
      • Determine when to use A/B tests, causal inference, and machine learning
      • Explain and assess objectives, assumptions, risks, and limitations
      • Determine if you have enough variables for your analysis


      It''s possible to predict events without knowing what causes them. Understanding causality allows you both to make data-driven predictions and also intervene to affect the outcomes. Causal Inference for Data Science shows you how to build data science tools that can identify the root cause of trends and events. You''ll learn how to interpret historical data, understand customer behaviors, and empower management to apply optimal decisions.

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