审计统计抽样技术方法研究与设计运行
发布时间：2019-03-28 06:31
【摘要】： 随着我国社会经济的快速发展和数字化时代的到来，各行各业大量、超大量的数据信息对审计工作提出了更高的要求。国家和社会审计面临着被审计对象信息量大，范围广，而审计人员和时间有限，审计责任加大，审计风险无法回避的现实，单一依靠审计人员经验判断的传统审计方法已经不能适应社会经济快速发展的需要，尤其是随着以真实性为基础的财政、金融、企业等项审计的深化，在上述情况下，审计人员在规定时间内对大量会计信息进行全部审计，并回答被审对象的资产、负债、损益的真实性问题是不可能的。采用非统计抽样虽然容易操作，但审计风险太大，难以对总体作出评价。而采用审计统计抽样方法，则可以大幅度提高审计效率，降低成本，达到审计目的。 本文针对目前从我国国情出发，理论联系实际，利用国内理论研究和审计实践成果，借鉴国外理论经验，运用概率论和数理统计理论，，在统计抽样如何与审计理论、实务相结合、其数学模型耦合、实际操作步骤及规范、如何使统计抽样在审计中的应用变的简单切实可行等方面展开了较深入系统的研究，并据此提出了我国审计技术与方法的部分标准和参数。 实践是检验真理的唯一标准，因此本课题在各审计现场进行了大量的测试和实际应用，对审计统计抽样的技术与方法进行反复验证，听取一线审计人员的宝贵意见。同时，注意在审计现场进行广泛的数据采集工作，为研究工作提供了大量基础数据。通过上述研究和实践，为本论文的编写提供了大量的素材和案例，并使本课题的正确性从实践上得到了论证。
[Abstract]:With the rapid development of China's social economy and the arrival of the digital era, a large number of industries, super large amounts of data and information put forward higher requirements for audit work. The state and social audit is faced with the fact that there is a large amount of information and a wide range of objects to be audited, while the auditor and time are limited, the audit responsibility is increased, and the audit risk cannot be evaded. The traditional audit method, which relies on the experience of auditors, can no longer meet the needs of the rapid development of social economy, especially with the deepening of the audit of finance, finance and enterprises based on authenticity. Under the above circumstances, the traditional audit method has not been able to meet the needs of the rapid development of the social economy. It is impossible for auditors to audit a large amount of accounting information and answer the question of the authenticity of assets liabilities and profits and losses of the subject under review. Although the use of non-statistical sampling is easy to operate, but audit risk is too large to evaluate the overall. The sampling method of audit statistics can greatly improve the audit efficiency, reduce the cost, and achieve the audit purpose. In view of the current situation of our country, combining theory with practice, using domestic theoretical research and auditing practice results, drawing lessons from foreign theoretical experience, using probability theory and mathematical statistics theory, how to use statistical sampling and auditing theory, Combined with practice, its mathematical model coupling, practical operation steps and norms, how to make the application of statistical sampling in audit become simple and feasible, etc., has carried out a more in-depth and systematic research. On this basis, some standards and parameters of audit techniques and methods in China are put forward. Practice is the only criterion for testing the truth, so this subject has carried out a lot of tests and practical applications in various audit sites, repeatedly verified the techniques and methods of sampling audit statistics, and listened to the valuable opinions of the first-line auditors. At the same time, attention is paid to the extensive data collection work in the audit site, which provides a lot of basic data for the research work. Through the above-mentioned research and practice, this paper provides a large number of materials and cases for the compilation of this paper, and makes the correctness of this topic proved from the practical point of view.
【学位授予单位】：湖南大学
【学位级别】：硕士
【学位授予年份】：2001
【分类号】：F239.1
本文编号：2448624
[Abstract]:With the rapid development of China's social economy and the arrival of the digital era, a large number of industries, super large amounts of data and information put forward higher requirements for audit work. The state and social audit is faced with the fact that there is a large amount of information and a wide range of objects to be audited, while the auditor and time are limited, the audit responsibility is increased, and the audit risk cannot be evaded. The traditional audit method, which relies on the experience of auditors, can no longer meet the needs of the rapid development of social economy, especially with the deepening of the audit of finance, finance and enterprises based on authenticity. Under the above circumstances, the traditional audit method has not been able to meet the needs of the rapid development of the social economy. It is impossible for auditors to audit a large amount of accounting information and answer the question of the authenticity of assets liabilities and profits and losses of the subject under review. Although the use of non-statistical sampling is easy to operate, but audit risk is too large to evaluate the overall. The sampling method of audit statistics can greatly improve the audit efficiency, reduce the cost, and achieve the audit purpose. In view of the current situation of our country, combining theory with practice, using domestic theoretical research and auditing practice results, drawing lessons from foreign theoretical experience, using probability theory and mathematical statistics theory, how to use statistical sampling and auditing theory, Combined with practice, its mathematical model coupling, practical operation steps and norms, how to make the application of statistical sampling in audit become simple and feasible, etc., has carried out a more in-depth and systematic research. On this basis, some standards and parameters of audit techniques and methods in China are put forward. Practice is the only criterion for testing the truth, so this subject has carried out a lot of tests and practical applications in various audit sites, repeatedly verified the techniques and methods of sampling audit statistics, and listened to the valuable opinions of the first-line auditors. At the same time, attention is paid to the extensive data collection work in the audit site, which provides a lot of basic data for the research work. Through the above-mentioned research and practice, this paper provides a large number of materials and cases for the compilation of this paper, and makes the correctness of this topic proved from the practical point of view.
【学位授予单位】：湖南大学
【学位级别】：硕士
【学位授予年份】：2001
【分类号】：F239.1
【引证文献】
相关硕士学位论文 前2条
1 王吉;基于审计决策支持系统的抽样技术研究[D];哈尔滨工业大学;2006年
2 汤晓超;基于数据挖掘技术的审计抽样系统开发和研究[D];江苏大学;2010年
本文编号：2448624
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