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Book Description

"Data is here, it's growing, and it's powerful." Author Cathy O'Neil argues that the right approach to data is skeptical, not cynical––it understands that, while powerful, data science tools often fail. Data is nuanced, and "a really excellent skeptic puts the term 'science' into 'data science.'" The big data revolution shouldn't be dismissed as hype, but current data science tools and models shouldn't be hailed as the end-all-be-all, either.

Table of Contents

  1. On Being a Data Skeptic
    1. Skeptic, Not Cynic
    2. The Audience
    3. Trusting Data Too Much
      1. 1) People Get Addicted to Metrics
      2. 2) Too Much Focus on Numbers, Not Enough on Behaviors
      3. 3) People Frame the Problem Incorrectly
      4. 4) People Ignore Perverse Incentives
    4. The Smell Test of Big Data
    5. Trusting Data Too Little
      1. 1) People Don’t Use Math to Estimate Value
      2. 2) Putting the Quant in the Back Room
      3. 3) Interpreting Skepticism as Negativity
      4. 4) Ignoring Wider Cultural Consequences
    6. The Sniff Test for Big Data
    7. Conclusion
  2. About the Author
  3. Copyright
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