David Spiegelhalter shifts the focus of statistical analysis away from mechanical calculations and toward the logic of problem-solving. He uses real-world examples, such as the survival rates of children undergoing heart surgery or the patterns of a notorious serial killer, to demonstrate how to interpret uncertainty and variation. The text explains core concepts like p-values, regression, and algorithmic bias by showing how they function in daily headlines rather than in isolated equations. Spiegelhalter emphasizes the PPDAC cycle—Problem, Plan, Data, Analysis, Conclusion—to teach readers how to scrutinize the origin and quality of numbers before drawing inferences.
This book is for students, journalists, and professionals who encounter data but lack a formal mathematical background. Readers gain the ability to spot manipulated graphics and recognize when a correlation does not imply a causal link. By the end, the reader possesses a toolkit for identifying the limitations of scientific studies and can better navigate a world saturated with complex metrics. It provides the literacy required to evaluate risks and make informed decisions based on evidence rather than intuition.
- Published
- 2019
- Language
- EN
