During a network security review, the system log indicates an unusually high number of unsuccessful login attempts.
Which of the following sampling techniques is MOST appropriate for selecting a sample of user IDs for further investigation?
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A. B. C. D.A.
The appropriate sampling technique for selecting a sample of user IDs for further investigation based on the system log's indication of an unusually high number of unsuccessful login attempts is attribute sampling.
Attribute sampling is a sampling method that involves identifying a characteristic of interest (in this case, unsuccessful login attempts) and selecting a sample to determine whether that characteristic exists or not. The population in this scenario would be all user IDs, and the characteristic of interest would be whether or not there are any unsuccessful login attempts associated with each user ID.
Attribute sampling is used when the auditor wants to determine the rate of occurrence of a specific attribute in a population. This technique involves randomly selecting a sample of items from the population and examining each one to determine whether it possesses the attribute of interest. The results of the sample are then used to estimate the rate of occurrence of the attribute in the entire population.
Other sampling techniques mentioned in the question are not appropriate for this scenario. Stratified sampling is used when the population can be divided into subpopulations that are homogeneous with respect to the characteristic of interest. Monetary unit sampling and variable sampling are used to estimate monetary amounts and numerical values, respectively, and are not applicable to this scenario.
In summary, attribute sampling is the most appropriate sampling technique for selecting a sample of user IDs for further investigation in this scenario.