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ABSTRACT This paper is a review of simulation techniques used to solve the probability distribution properties of life insurance gains and losses resulting from random behavior of the mortality element. The simulation methods of Benjamin are extended and adapted to situations having further random behavior from a withdrawal element, as in individual life insurance. Examples are given for an assumed insurance portfolio in the one-year term case. An exercise compares traditional methods with a simulation technique in making probability statements about large losses. A twenty-year asset share calculation is simulated, in which the usual asset share appears as the expected value of a distribution of possible asset share results. [ABSTRACT FROM AUTHOR]

The article examines a cost-volume-profit (CVP) model that does not require a sales volume or any other variate figure. Most cost-volume-profit analyses are based on a certainty-assuming model in which price (P), variable cost per unit (V), sales volume (X), and total fixed cost (F) of a single-product firm, or one product of a multiproduct firm, are known. In most models, sales volume is made a variable, with the other variables held constant, allowing researchers to determine the probabilities of achieving various target profit levels, break-even sales, and possible loss levels. In this multiproduct CVP analysis with uncertainty, the interdependency of product demand is accounted for. With most of these CVP analyses under conditions of uncertainty, one can assume that the random variable for sales volume is known. The main advantage of using this CVP model is that the distribution function of the sum P need not be known.

This article presents a reply to a comment on a paper that presented a utility function in order to examine the variables that explain the required rate of return on stock for an investor. The author addresses the notion that he assumes a cubic utility function in the theoretical portion of his paper. The author states that he uses a general utility function and attempts to clarify the misunderstanding of this application. The author also defends the variables that are presented in the paper, noting that they were necessary in the development of a testable model.

The article assesses the significance of accounting variances. The author discusses the consideration of the aspects of control problem and the distinction between costs and probability distributions. The author stats that one of the problems that frequently arises in the control of a large decentralized corporation is the assessment, of periodic financial reports issued by its various operating divisions and departments. The article also discusses the implementation of digital computers and also provides several equations. [ABSTRACT FROM AUTHOR]

PERT, as an aid in planning for project managers, has been widely accepted, but as yet there appears to be a wide gap between the user's apparent impression of the underlying assumptions and the theoretical assumptions. This paper points out some of the more common misconceptions and their implications upon the total project. The Beta distribution as the underlying probability distribution is evaluated as to first, the overall effects of the inherent errors that are imposed by the basic PERT assumptions, and second, the effects, from a probability distribution viewpoint, of some of the more common PERT misconceptions. Finally, several alternatives to the basic PERT methodology are explored, both from the theoretical and practical viewpoints. [ABSTRACT FROM AUTHOR]

Copyright of Canadian Journal of Statistics is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Despite the key role that subjective probabilities play in decisions made under conditions of uncertainty, little is known about the ability of probability assessors in developing these estimates. A literature survey is followed by a review of results from a continuing series of experiments designed to investigate the external accuracy of subjectively assessed probability distributions. Initial findings confirm that probability assessments provided by untrained assessors are of questionable value in predicting the distribution of actual outcomes of uncertain events. Particular difficulty is encountered when subjects attempt to quantify the extremes of their subjective distributions. The impact of extended assessor training and hypotheses regarding the effects of variation in the assessor's information level and the complexity of the assessment task are explored. Implications for applied decision making are drawn, and directions for future investigations are suggested. [ABSTRACT FROM AUTHOR]

Copyright of Canadian Journal of Statistics is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Lindley's measure of experimental information is utilized to determine the optimal sample-size that is required to obtain a prescribed level of accuracy about the parameter of a binomial distribution. The measure is expressed through its approximate limiting relationship to the posterior variance of the parameter, and a simple application of the methodology is presented. [ABSTRACT FROM AUTHOR]

The article examines the possibility to prove any general statements about historical facts. The absurdity of counting incongruous things is brought out in the old story of the army contractor who offered to supply pies composed in equal proportions of rabbit and horse. On the contrary a valuable method of counting unequal objects, namely stars, was introduced by the ancient astronomers, Ptolemy and Al Sufi. They first graded the stars into six classes according to their conspicuousness and afterwards counted the number of stars in each class. Modern astronomers still use refinements of Ptolemy's method. Sorokin's measure of an internal disturbance, such as a civil war, is a geometric mean of four estimates of its importance depending severally on its social area, its duration, its intensity as indicated by the amount of violence and the number of sociopolitical changes and the numbers of people actively engaged. When a student, unfamiliar with the detailed events and discussions, has read an authoritative summary of why any particular war occurred, he is likely to feel that events could not have happened otherwise. On the contrary, when one takes a comprehensive list of wars and analyzes it by a suitable technique, a familiar statistical distribution appears and thereby calls attention to the random and chance aspect of events. The method of analysis can be explained by its application to Wright's list. Wright lists four of the largest wars both as wholes and as parts. The parts were preferred, because that choice made the wars less unequal in size. A list of calendar years was prepared. Each war was taken in turn and a mark was placed against the year in which it began. This distribution of years can be fitted with a formula named after S. D. Poisson, a French mathematician who published it in A.D. 1837.