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Estimating the Total Overstatement Error in Accounting Populations

 

作者: StephenE. Fienberg,   John Neter,   R.A. Leitch,  

 

期刊: Journal of the American Statistical Association  （Taylor Available online 1977）
卷期: Volume 72, issue 358  

页码: 295-302

 

ISSN:0162-1459

 

年代: 1977

 

DOI:10.1080/01621459.1977.10480993

 

出版商: Taylor & Francis Group

 

关键词: Accounting populations;Confidence bounds for overstatement errors;Multinomial distribution;Overstatement error bounds;Stringer bound

 

数据来源: Taylor

 

摘要:

Auditors wishing to estimate the total amount of errors in a set of accounts have tended to use estimation procedures which rely on approximate normality for large sample sizes. Since this reliance is often not well-founded for sample sizes used in auditing practice, efforts have been made to circumvent this difficulty. This paper will briefly describe these efforts and then present a new approach based on the multinomial probability distribution which yields confidence bounds with known confidence levels for all sample sizes.

 

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