The period cost concept divides cost data into two broad categories, firstly, "Period" costs which are those costs related to time, i.e., those costs which expire with the passage of time rather than with the volume of business activity, and secondly, "product" costs which include those costs which relate to the product being produced, i.e., those costs which are directly affected by the volume of business activity. Under the period cost concept as it relates to income measurement only variable manufacturing costs are considered inventoriable while fixed manufacturing costs as well as selling and administrative costs are period costs. In general the accounting profession does not accept for income measurement purposes the treatment of fixed manufacturing costs as period costs. Conversely the accounting profession has accepted for many years a period cost approach to the handling of selling and administrative costs. In this article the authors will show that the period cost concept is not appropriate for purposes of income measurement. It is the intention of this article to show that categorizations of cost such as period costs vs. product costs are not relevant to the process of income measurement.

The article presents a reply to authors John F. Kottas and Hon-Shiang Lau, on the appropriate size of samples in &chi 2 tests. The paper by FHN falls into the realm of accounting risk analysis. In risk analysis, it attempt to incorporate uncertainty into the decision process and, at the same time, try to make the analysis as simple as possible so that it can be understood by the manager and so that it can be done by those with elementary knowledge in statistics and mathematics. There is, therefore, a need in risk analysis to reduce intractible functions to reasonable approximations, preferably to the normal approximation as it is the most familiar and easiest distribution for the practitioner to use. In simulation experiments, the record has been that the choice of sample size was, for the most part, arbitrary. Better yet would be a choice based on the fulfillment of some important criteria of validity, for example, that the minimum expected frequency in a cell be no less than one in a chi-square goodness-of-fit test.

This article presents information related to the article "Cost-Volume-Profit Analysis Under Conditions of Uncertainty," by researchers Robert K. Jaedicke and Alexander A. Robichek. The fact that the traditional "cost-volume profit analysis" does not include adjustments for uncertainty severely limits its usefulness. Jaedicke and Robichek explain that if a firm is considering the introduction of two new products with the same expected fixed costs, the same expected selling price per unit, the same expected variable costs per unit and the same expected breakeven sales volume, one may be misled to think that the two products are equally desirable. This is not true for one good reason: determining which product is more desirable depends upon the frequency distributions of all the variables that influence profit, not just their expected values. Furthermore, it is more instructive to compare two profit distributions not only by their expected values but also in terms of their variances. Use of the Jaedicke-Robichek model enables one to compute the expected value and the standard deviation of profit for a given product. This information enables a manager to estimate the probability of achieving the breakeven point, as well as the probability of achieving any level of profit or loss.

Reviews the book "Cost and Budget Analysis," by John Dearden.