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 - Moon Na - Goodreads
I used this book while attending the introduction to statistical method for economists course in my bachelor, however, just finished it recently. De Groot wrote it in detailed and clear way. Among ... Read full review
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
Random Variables and Distributions
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