000			a
999			_c34874 _d34874
008			251005b xxu||||| |||| 00| 0 eng d
020			_a 9789332573871
082			_a519.2 _bDEG
100			_aDeGroot, Morris H.
245			_aProbability and Statistics
250			_a4th ed.
260			_bPearson, _c2016 _aNoida :
300			_a829 p. ; _bill., _c26 cm.
365			_b2100.00 _c₹ _d01
504			_aIncludes bibliographical references and index.
520			_aThe 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.
650			_aScience and Nature
650			_aMathematical Statistics
650			_aProbabilities
650			_aProbabilities and Applied Mathematics
650			_aLinear Statistics Model
700			_aSchervish, Mark
942			_2ddc _cBK