Pociecha J. New directions of business statistics in finance and auditing

The classical approach in applications of business statistics offers a various statistical techniques for solving economic and managerial problems. A typical handbook in business statistics contains regular presentation of statistical techniques, starting from descriptive statistics through regression analysis, probability theory, statistical inference to time series analysis. This type of presentation is not useful for users, because on the first place put statistical methods, but not problems which could be solved using statistical methods. The proper approach is first to define a real economic or managerial problem and then, look for an appropriate statistical techniques. Problem oriented approach is presented in this paper. As the first example, a real problem in auditing is presented. On which principle an auditor can decide that considered financial statement gives a true and far view on financial situation and results of economic activity of investigated firm. A useful tools for answering the question are tests of controls and significant tests in auditing. All this methods based on statistical approach, but not a classical one. The specificity of these methods are presented in the paper. As the second example an important economic problem of bankruptcy prediction has been presented. The knowledge about risk of firm collapsing is very important for owners, managerial staff, employees, banks and other market institutions. The basic methods for firms bankruptcy prediction are: multivariate discriminante analysis models, Logit models and neural networks models. A history of mentioned above methods is presented.

Keywords: business statistics, statistical methods in auditing, statistical tests in auditing, bankruptcy prediction models.


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