Probability and StatisticsThe revision of this well-respected text presents a balance of the classical and Bayesian methods. The theoretical and practical sides of both probability and statistics are considered. New content areas include the Vorel- Kolmogorov Paradox, Confidence Bands for the Regression Line, the Correction for Continuity, and the Delta Method. |
Contents
Introduction to Probability | 1 |
Conditional Probability | 57 |
Random Variables and Distributions | 97 |
Copyright | |
11 other sections not shown
Common terms and phrases
a₁ assume B₁ B₂ balls Bayes estimator Bernoulli distribution beta distribution binomial distribution c₁ c₂ conditions of Exercise Consider continuous distribution degrees of freedom determine the probability Determine the value discrete distribution distribution with mean distribution with parameters Example exponential distribution following hypotheses follows from Eq form a random Furthermore gamma distribution given by Eq given value H₁ Hence integer joint distribution joint p.d.f. level of significance likelihood function linear mean µ null hypothesis observed values obtained outcomes P₁ Poisson distribution possible values posterior distribution Pr(A Pr(B Pr(X Pr(Y prior distribution problem random sample random variables X₁ regression rejected sample mean selected at random specified standard normal distribution statistician sufficient statistic Suppose that X₁ Table test procedure Theorem tossed total number unbiased estimator uniform distribution unknown Var(X variance o² X₂ x² distribution Y₁