Beginning with the historical background of probability theory, this thoroughly revised text examines all important aspects of mathematical probability - including random variables, probability distributions, characteristic and generating functions, stochatic convergence, and limit theorems - and provides an introduction to various types of statistical problems, covering the broad range of statistical inference.;Requiring a prerequisite in calculus for complete understanding of the topics discussed, the Second Edition contains new material on: univariate distributions; multivariate distributions; large-sample methods; decision theory; and applications of ANOVA.;A primary text for a year-long undergraduate course in statistics (but easily adapted for a one-semester course in probability only), Introduction to Probability and Statistics is for undergraduate students in a wide range of disciplines-statistics, probability, mathematics, social science, economics, engineering, agriculture, biometry, and education.
general concepts of probability
random variables, probability distributions, and characteristic functions, stochastic convergence and limit theorems
concepts of statistics
order statistics and related distributions
statistical inference - parametric point estimation
testing of statistical hypotheses
statistical decision theory
general linear hypothesis and analysis of variance
some applications of analysis of variance
appendix A - vectors and matrices
appendix B - statistical tables.