PROFESSORS Friedman and Meiselman' recently have reported that a simple theory model describes aggregate consumption more accurately than a simple autonomous expenditure model. They believe this result is evidence that the quantity theory is a better description of the American economy than the autonomous expenditure or Keynesian theory.2 If their interpretation were correct, the Friedman-Meiselman paper would be one of the most significant economic studies in many years. But it is not correct. Friedman and Meiselman have represented the autonomous expenditure theory in a very unorthodox form. Their statistical comparisons are extremely sensitive to how the autonomous expenditure theory is represented. Below, I employ a more conventional representation of the autonomous expenditure theory and demonstrate why Friedman and Meiselman's tests are misleading. Further, using this conventional model and some of their data, little empirical evidence is found which favors the theory. Finally some other conceptual weaknesses of the Friedman-Meiselman tests are illustrated. Briefly, Friedman and Meiselman compare simple, partial, and multiple correlation coefficients obtained from the following equations, estimated from annual (1897-1958) and quarterly (1945-1958) data for the United States: C=al+8(A (1) C=a2 +82M (2) C = a3+/33A +13P (3) C = a4 +84M+y4P (4) C = a5 + 35A + 85M (5) C = a6 + 86A + 86M + Y6P (6)

The article illustrates the use of the term heuristics and thereby facilitate retention, and to provide an appreciation as to the limitations as well as the advantages of this approach to problem solving. Students of management and accountants concerned with computer technology and its application to the problems of business administration have probably seen the terms "heuristic" and "heuristics" in the literature used as an adjective and a noun. A heuristic model, written as a computer program, simulates the procedures used in choosing investment policies for accounts, in evaluating the alternatives presented by the market, and in selecting the required portfolios. Heuristics are important as they often lead quickly to solutions that one would otherwise reach much more expensively by analytic techniques.

A sound knowledge of cost-volume-profit behavior and cost interrelationships is essential to many business decisions. Information which is easily understood but may not represent reality can lead to costly errors in judgment in business decisions. The management accountant certainly has a responsibility to provide management with something more than simply data. He has a responsibility to provide analyzed data, or useful information, for specific purposes. Yet he has a grave responsibility to avoid employing oversimplified techniques, or partial analysis, which may be misused or misunderstood by management. This article serves four purposes. First, to present the application and limitations of the Scatter Graph and Least Squares methods of studying the cost-volume-profit relationships of a company. Second, to present the possible weaknesses or limitations of Break-even Analysis and Profit Graphs. Third, to review some of the major statistical techniques of evaluating the significance of relationships. Fourth, to present the application of Multiple Regression Analysis, with the aid of a computer, to determine the cost-volume-profit relationship.