Business students, social sciences, beginners. 2.2 Intermediate Level (Calculus-based) Rigorous introduction suitable for STEM majors. Requires knowledge of differentiation and integration.
Engineering, computer science, and mathematics majors. 2.3 Advanced Level (Measure theory and proof-based) For graduate students or advanced undergraduates in statistics/mathematics. libro probabilidad y estadistica
| Title | Author(s) | Key Features | | :--- | :--- | :--- | | | George Casella & Roger Berger | The gold standard for graduate-level inference (MLE, UMVUE, hypothesis tests). | | Probability and Measure | Patrick Billingsley | Advanced probability theory; requires real analysis. | | All of Statistics | Larry Wasserman | Concise coverage of both probability and statistical inference. | Business students, social sciences, beginners
| Title | Author(s) | Key Features | | :--- | :--- | :--- | | | Jay L. Devore | Clear exposition, real engineering applications, many solved examples. | | Mathematical Statistics with Applications | Wackerly, Mendenhall, Scheaffer | Balance between theory and applications; classic problems. | | Introduction to Probability and Statistics | William Mendenhall | Focus on inference and hypothesis testing. | Engineering, computer science, and mathematics majors