Probability and Statistics

The Revision Of This Well-respected Text Presents A Balanced Approach Of The Classical And Bayesian Methods And Now Includes A New Chapter On Simulation (including Markov Chain Monte Carlo And The Bootstrap), Expanded Coverage Of Residual Analysis In Linear Models, And More Examples Using Real Data. 1. Introduction To Probability -- 2. Conditional Probability -- 3. Random Variables And Distributions -- 4. Expectation -- 5. Special Distributions -- 6. Estimation -- 7. Sampling Distributions Of Estimators -- 8. Testing Hypotheses -- 9. Categorical Data And Nonparametric Methods -- 10. Linear Statistical Models -- 11. Simulation. Morris H. Degroot, Mark J. Schervish. Includes Bibliographical References (p. 801-806) And Index.