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Mathematical Methods of Statistics (PMS-9), Volume 9
Volume 26 in the series
Princeton Mathematical Series
In the series
Princeton Landmarks in Mathematics and Physics
- Language: English
- Publisher: Princeton University Press
- Copyright year: 1946
- Audience: Professional and scholarly;College/higher education;
- Pages
- Main content: 575
- Keywords: Probability; Estimation; Variable (mathematics); Random variable; Parameter; Normal distribution; Theorem; Quantity; Sign (mathematics); Empirical distribution function; Characteristic function (probability theory); Probability distribution; Distribution function; Summation; Statistical hypothesis testing; Variance; Distribution (mathematics); Moment (mathematics); Statistical regularity; Joint probability distribution; Axiom; Calculation; Set (mathematics); Proportionality (mathematics); Interval (mathematics); Measure (mathematics); Logarithmic derivative; Parity (mathematics); Mathematical induction; Correlation coefficient; Bounded set (topological vector space); Series (mathematics); Lebesgue measure; Bias of an estimator; Borel set; Degeneracy (mathematics); Set function; Degrees of freedom (statistics); Method of moments (statistics); Estimation theory; Probability theory; Weighted arithmetic mean; Mathematical statistics; Addition theorem; Binomial theorem; Arithmetic mean; Minor (linear algebra); Poisson distribution; Statistical Science; Sampling (statistics); Realization (probability); Scientific notation; Linear regression; Metric space; Dimension; Mathematical theory; Confidence interval; Convergence of random variables; Z-test; Bolzano–Weierstrass theorem; Independence (probability theory); Mathematical analysis; Statistical theory; Moment matrix; Laplace distribution; Limit (mathematics); Coefficient; Uniform distribution (discrete); Binomial distribution; Logarithm; Lebesgue integration; Subset; Logarithmic scale; Sample space; Riemann integral; Commutative property; Lebesgue–Stieltjes integration; Statistical inference; A priori probability; Transfinite number; Diagram (category theory); Central moment; Additive function; Theory; Maxima and minima; Equation; Bayes' theorem; Identity matrix; Statistic; Analysis of covariance; Cartesian product; Marginal distribution; Numerical analysis; Likelihood function; Invertible matrix; Matrix (mathematics); Standard deviation; Inverse probability; Mathematics; Characteristic polynomial
eBook
- Published: June 2, 2016
- ISBN: 9781400883868
