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Theory and Methods of Statistics covers essential topics for advanced graduate students and professional research statisticians. This comprehensive resource covers many important… Read more
SUSTAINABLE DEVELOPMENT
Save up to 30% on top Physical Sciences & Engineering titles!
Theory and Methods of Statistics covers essential topics for advanced graduate students and professional research statisticians. This comprehensive resource covers many important areas in one manageable volume, including core subjects such as probability theory, mathematical statistics, and linear models, and various special topics, including nonparametrics, curve estimation, multivariate analysis, time series, and resampling. The book presents subjects such as "maximum likelihood and sufficiency," and is written with an intuitive, heuristic approach to build reader comprehension. It also includes many probability inequalities that are not only useful in the context of this text, but also as a resource for investigating convergence of statistical procedures.
Graduate (Masters/PhD) students and research statisticians.
1: Probability Theory
2: Some Common Probability Distributions
3: Infinite Sequences of Random Variables and Their Convergence Properties
4: Basic Concepts of Statistical Inference
5: Point Estimation in Parametric Models
6: Hypothesis Testing
7: Methods Based on Likelihood and Their Asymptotic properties
8: Distribution-Free Tests for Hypothesis Testing in Nonparametric Families
9: Curve Estimation
10: Statistical Functionals and Their Use in Robust Estimation
11: Linear Models
12: Multivariate Analysis
13: Time Series
Appendix A: Results From Analysis and Probability
Appendix B: Basic Results From Matrix Algebra
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