Нові напрями бізнес-статистики у фінансах та аудиті
Тип публікації :
Стаття
Дата випуску :
10 вересня 2011 р.
Автор(и) :
Pociecha, J.
Cracow University of Economics (Poland)
Мова основного тексту :
Ukrainian
eKNUTSHIR URL :
Випуск :
129
ISSN :
1728-2667
Початкова сторінка :
17
Кінцева сторінка :
20
Цитування :
[APA 7] Pociecha, J. (2011). New directions of business statistics in finance and auditing. Вісник Київського національного університету імені Тараса Шевченка. Економіка, (129), 17–20.
[ДСТУ] Pociecha J. New directions of business statistics in finance and auditing. Вісник Київського національного університету імені Тараса Шевченка. Економіка. 2011. Вип. 129. С. 17—20.
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.
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.
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