Management Accounting: A Review of Contemporary Developments by Robert W. Scapens

By Robert W. Scapens

Studies from first version: 'This a complete survey of released examine and said improvement in administration accounting over the last twenty years. As such, it's a priceless and simply assimilated 'state of the artwork' review.' David Fanning, British Accounting assessment 'For somebody who desires to understand the place administration accounting has been going, Scapens is a superb guide...I suggest it to somebody who desires to meet up with what has been occurring in administration accounting conception. in truth, i do know of no larger technique to do so.' David Solomons, Accounting and enterprise learn

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It is important to recognise the nature of these properties, because if they are not met in a particular regression problem, the estimates of a and b will be affected. The following are the assumed properties: (i) The mean of the error term is zero. (ii) The values of the error terms e; and ei associated with any two values of X are independent. (iii) There is a constant variance of the error term for all observed values of X. The independence and constant variance properties of the error term require careful consideration, as they could be violated in a number of accounting contexts.

The notion of 'conditional truth' is appropriate because management accounting, as described above, implies that different costs are needed for different purposes, or in other words, accounting information depends on the information needs of managers. Thus, in developing management accounting concepts and techniques researchers had to identify managers' information needs. In general, this The Conventional Wisdom 23 meant constructing decision models to indicate how decisions are, or should be, made.

3. In that case, the regression equation takes the form Y=a, where a is the mean of the Y observations. In such a case, the value of b is zero and the regression has no explanatory power- for any value of X, the best estimate of Y is the mean of the observed values of Y. Two approaches are available to test the adequacy of the linear model: (i) The hypothesis that the value of b in the regression equation is significantly different from zero can be tested. (ii) The variation in the dependent variable which is explained by the model can be analysed - this is known as the analysis of variance.

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