Truth or truthiness : distinguishing fact from fiction by learning to think like a data scientist

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The book "**Truth or Truthiness: Distinguishing Fact from Fiction by Learning to Think Like a Data Scientist**" by **Howard Wainer** explores several themes and topics. These can help you draw connections to other books in a library:

*   **Skeptical Mindset**: The book emphasizes the importance of approaching information with skepticism and critical thinking, which are key to exposing deception and nonsense. 【1】【2】
    *   Connects to books on: Critical thinking, logic, philosophy, and skepticism.
*   **Statistical Literacy**: The book aims to promote understanding of statistics and probability, arguing that an understanding of data science is essential for informed citizenship. 【3】【4】
    *   Connects to books on: Statistics, data analysis, probability, and quantitative reasoning.
*   **Distinguishing Fact from Fiction**: A core theme is the ability to differentiate between reliable information and misinformation, using the tools of a data scientist. 【1】【5】
    *   Connects to books on: Media literacy, fact-checking, journalism, and research methods.
*   **Data Science Applications**: The book uses real-world examples from fields like education and medicine to illustrate how data science can be applied to evaluate claims and make better decisions. 【3】【6】
    *   Connects to books on: Data science, data mining, machine learning, and applications of data analysis in various fields (e.g., healthcare, education, economics).
*   **Causal Inference**: The book uses causal inference to evaluate evidence and claims in various fields. 【6】
    *   Connects to books on: Causality, research design, econometrics, and epidemiology.
*   **Truthiness**: The book addresses the concept of "truthiness," where claims are made without regard to evidence or facts, relying instead on intuition or feelings. 【7】
    *   Connects to books on: Cognitive biases, rhetoric, propaganda, and the psychology of belief.