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. 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.
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Review: Probability and StatisticsUser Review - Ben - Goodreads
Best book I have read on both subjects. Just the right amount of math for someone that knows calc (doesn't need a hand held), but isn't a mathematicians (very simple proofs). Read full review
Introduction to probability and mathematical statistics
Lee J. Bain,Max Engelhardt
Snippet view - 1987
Introduction to Probability
Random Variables and Distributions
11 other sections not shown