Charles Wheelan explains the logical foundations of statistical analysis by removing the complex mathematical notation that often obscures the core concepts. He uses real-world examples, such as Netflix’s recommendation engine and the link between smoking and cancer, to illustrate how descriptive statistics, probability, and correlation function in everyday life. The text breaks down technical frameworks like the Central Limit Theorem and regression analysis, demonstrating how researchers use these tools to identify patterns or isolate variables. Wheelan also details how data can be manipulated through biased sampling or the misunderstanding of causation versus correlation.
This book is intended for professionals, students, and citizens who encounter data in their careers but lack a formal background in advanced mathematics. Readers learn to interpret standard deviation, provide healthy skepticism toward polling numbers, and recognize common pitfalls like the Monty Hall problem. The audience gains the ability to evaluate the validity of quantitative claims found in news reports and business presentations. Rather than memorizing formulas, the reader walks away with a functional intuition for how data science informs public policy and corporate decision-making.
- Published
- 2012
- Language
- EN
