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References: Interpreting Validation Evidence

  1. Lean startup - Wikipedia - Covers the build-measure-learn loop and the formal distinction between a pivot (a structured course correction) and continuing on the current path, the central decision this chapter teaches how to make.

  2. Confirmation bias - Wikipedia - Explains the tendency to search for and interpret evidence in ways that confirm existing beliefs. Directly relevant to this chapter's core warning against reading a test result the way you hoped it would turn out.

  3. Falsifiability - Wikipedia - Covers Karl Popper's principle that a claim is only scientifically meaningful if evidence could prove it wrong. Clarifies why this chapter insists a test hypothesis must be a specific, falsifiable prediction.

  4. The Lean Startup (2011) - Eric Ries - Crown Business - Ries originated the build-measure-learn loop and formalized the pivot-or-persevere decision meeting as a recurring checkpoint, which is the direct source of this chapter's persevere, pivot, and kill framework.

  5. The Mom Test (2013) - Rob Fitzpatrick - Robfitz Ltd - Fitzpatrick is credited with the technique of distinguishing what people actually do from the polite, non-committal things they say, clarifying why this chapter treats a customer payment signal as categorically stronger evidence than a compliment.

  6. Confirmation Bias in UX - Nielsen Norman Group - Explains how researchers unintentionally favor data that supports their existing assumptions, and how to reduce that bias, reinforcing the chapter's discipline of reading evidence honestly.

  7. Do Pivots Matter? - Steve Blank - Argues that a genuine pivot means changing a specific business model component, not just the product, echoing this chapter's definition of a pivot as changing one significant element while keeping what evidence has supported.

  8. The Discipline of Business Experimentation - Harvard Business Review - Shows how companies misread test results as statistical noise rather than real signal, illustrating why this chapter separates a raw test result from its interpretation.

  9. Don't Build When You Build-Measure-Learn - Strategyzer - Explains how to achieve maximum learning for minimum effort using low-cost MVP formats, directly supporting this chapter's concepts of the smallest testable version and low-capital testing.

  10. Act Like a Startup - MIT Sloan Management Review - Describes how startups learn as quickly and inexpensively as possible and embrace pivots rather than doubling down on a failing plan, reinforcing rapid experimentation and low-capital testing.