METHODS AND ALGORITHMS OF EQUIPROBABILITY STATISTICAL SAMPLING IN AUDIT

The presented study considers the relevance of implementing methods and algorithms of equal probability statistical sampling in audit. In the context of continuous development of our society, auditors face more and more problems in the process of their activities. In turn, statistical sampling allows auditors to formulate reasonable results based on the analysis of a limited number of elements, ensuring the representativeness and reliability of their conclusions. In addition, the work compares statistical and non-statistical sampling. In addition, some statistical sampling methods, such as simple random sampling, systematic sampling, stratified sampling and cluster sampling, their advantages and disadvantages, as well as problems that auditors may encounter when applying them, and proposals for solving these difficulties are considered in detail. In conclusion, the work notes the relationship between machine learning and statistical sampling, as well as their contribution to improving the quality and accuracy of audits.