Description: This paper highlights how the estimation procedure works in regards to annuities, including immediate life annuities.

Description: This paper defines a general model for arbitrary units and gives formulas for computing the variance and mean squared error of decrement estimators. It is observed that, in small studies, the mean squared error is reduced by counting lives, even if the probability of death depends somewhat on the amount of insurance. From Transactions of Society of Actuaries 1981, Vol. 33.

Description: Column highlighting education committee volunteers and the benefits of volunteering.

Description: This article is an update on the educational and qualification 2005

Description: Presented at October 1985 Annual Meeting. This session focused on three projects funded by the Actuarial Education and Research Fund: risk models, operations research applications for actuaries and probability modeling of losses.

Description: Stuart Klugman provides a preliminary education update as it pertains to Exams P/1, FM/2, and MLC.

Description: Actuaries use data, math, intuition, and domain expertise to make decisions under uncertainty. Bayesian models formalize the techniques many of us use every day. While many Bayesian models are impossible to solve analytically, new tools allow us to create rich Bayesian models and use computers to evaluate them quickly. In this session we will build several Bayesian models using Python and pymc3, a probabilistic programming language, to demonstrate Bayesian techniques that can be applied to actuarial work.

Description: This paper discusses the Bayesian graduation method of Kimeldorf and Jones and develops methods for managing four technical problems in their method. It also includes a discussion of the paper. From Transactions of Society of Actuaries 1977, Vol. 29.