| Sumario: | The article reviews *Applied Statistics with Python: Volume I: Introductory Statistics and Regression*, a textbook designed to integrate Python programming directly into the teaching of introductory statistics and regression. Targeted at undergraduate students across various disciplines, the book emphasizes computational literacy alongside statistical intuition, using real-world datasets and step-by-step coding examples to bridge theory and application. While it provides a clear and accessible foundation in descriptive statistics, probability, inference, and simple linear regression, the text offers limited coverage of inferential theory and model diagnostics, and focuses exclusively on Python, which may affect its adaptability in diverse instructional settings. Overall, the book serves as a practical resource for applied statistics education that prioritizes coding and interpretation over formal mathematical rigor.
|
|---|