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"Statistics, data, and statistical thinking -- Methods for describing sets of data -- Probability -- Random variables and probability distributions -- Continuous random variables -- Sampling distributions -- Inferences based on a single sample : estimation with confidence intervals -- Inferences based on a single sample : tests of hypotheses -- Inferences based on two samples : confidence intervals and tests of hypotheses -- Design of experiments and analysis of variance -- Categorical data analysis -- Simple linear regression -- Multiple regression and model building -- Methods for quality improvement : statistical process control (available on CD) -- Time series : descriptive analyses, models, and forecasting (available on CD) -- Nonparametric statistics (available on CD) -- Answers to selected exercises -- Index -- Credits "

""Preface Financial and actuarial modeling is an ever-changing field with an increased reliance on statistical techniques. This is seen in the changing of competency exams, especially at the upper levels, where topics include more statistical concepts and techniques. In the years since the first edition was published statistical techniques such as reliability measurement, simulation, regression, and Markov chain modeling have become more prominent. This influx in statistics has put an increased pressure on students to secure both strong mathematical and statistical backgrounds and the knowledge of statistical techniques in order to have successful careers. As in the first edition, this text approaches financial and actuarial modeling from a statistical point of view. The goal of this text is twofold. The first is to provide students and practitioners a source for required mathematical and statistical background. The second is to advance the application and theory of statistics in financial and actuarial modeling. This text presents a unified approach to both financial and actuarial modeling through the utilization of general status structures. Future timedependent financial actions are defined in terms of a status structure that may be either deterministic or stochastic. Deterministic status structures lead to classical interest and annuity models, investment pricing models, and aggregate claim models. Stochastic status structures are used to develop financial and actuarial models, such as surplus models, life insurance, and life annuity models. This edition is updated with the addition of nomenclature and notations standard to the actuarial field"--"

"This brief offers developments on Kalman filtering subject to general linear constraints. There are essentially three types of contributions, new proofs for results already established, new results within the subject, and applications in investment analysis and macroeconomics, where the proposed methods are illustrated and evaluated. The Brief has a short chapter on linear state space models and the Kalman filter. "