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Springer Texts in Statistics

This series offers fundamental and advanced texts covering a wide array of statistical topics. It is designed to serve as a valuable resource for students, researchers, and practitioners in the field. The books often include theoretical foundations, practical applications, and modern methodologies crucial for understanding and performing statistical analysis. The series is recognized for its clarity and scholarly rigor, making it indispensable for anyone seriously engaged with statistics.

Monte Carlo statistical methods
Testing Statistical Hypotheses

Recommended Reading Order

  1. Markov chain Monte Carlo methods were developed to provide the experimenter with realistic models. Written by two leading researchers, this up-to-date reference covers an important area of statistic which has many applications to engineering, aeronautics, biology, networks, and astronomy.

    Monte Carlo statistical methods