Probability and Statistics
DeGroot, Morris H.
Probability and Statistics - 4th ed. - Noida : Pearson, 2016 - 829 p. ; ill., 26 cm.
Includes bibliographical references and index.
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. Probability & Statisticswas written for a one or two semester probability and statistics course offered primarily at four-year institutions and taken mostly by sophomore and junior level students, majoring in mathematics or statistics. Calculus is a prerequisite, and a familiarity with the concepts and elementary properties of vectors and matrices is a plus. Introduction to Probability; Conditional Probability; Random Variables and Distribution; Expectation; Special Distributions; Estimation; Sampling Distributions of Estimators; Testing Hypotheses; Categorical Data and Nonparametric Methods; Linear Statistical Models; Simulation For all readers interested in probability and statistics.
9789332573871
Science and Nature
Mathematical Statistics
Probabilities
Probabilities and Applied Mathematics 
Linear Statistics Model
519.2 / DEG
Probability and Statistics - 4th ed. - Noida : Pearson, 2016 - 829 p. ; ill., 26 cm.
Includes bibliographical references and index.
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. Probability & Statisticswas written for a one or two semester probability and statistics course offered primarily at four-year institutions and taken mostly by sophomore and junior level students, majoring in mathematics or statistics. Calculus is a prerequisite, and a familiarity with the concepts and elementary properties of vectors and matrices is a plus. Introduction to Probability; Conditional Probability; Random Variables and Distribution; Expectation; Special Distributions; Estimation; Sampling Distributions of Estimators; Testing Hypotheses; Categorical Data and Nonparametric Methods; Linear Statistical Models; Simulation For all readers interested in probability and statistics.
9789332573871
Science and Nature
Mathematical Statistics
Probabilities
Probabilities and Applied Mathematics 
Linear Statistics Model
519.2 / DEG