Module F - Attributes sampling. In this module, you will be able to: Identify the objectives of attributes sampling, define deviation conditions, and define the population for an attributes sampling application; understand how various factors influence the size of an attributes sample; determine the sample size for an attributes sampling application. | Copyright © 2013 by The McGraw-Hill Companies, Inc. All rights reserved. McGraw-Hill/Irwin Module F Attributes Sampling Learning Objectives Identify the objectives of attributes sampling, define deviation conditions, and define the population for an attributes sampling application. Understand how various factors influence the size of an attributes sample. Determine the sample size for an attributes sampling application. Identify various methods of selecting an attributes sample. Evaluate the results of an attributes sampling application by determining the upper limit rate of deviation . Define sequential sampling and discovery sampling and identify when these types of sampling applications would be used. Understand how to apply nonstatistical sampling to attributes testing. Mod F- Attributes Sampling Used to estimate the extent to which a characteristic (attribute) exists within a population Used in tests of controls Mod F- Major Steps in attributes Sampling: Planning Determine the objective of sampling Define deviation conditions Define the population Mod F- Major Steps in attributes Sampling: Performing Determine sample size Select sample items Measure sample items Mod F- How to Determine Sample Size Select AICPA Sample Size table corresponding to desired risk of overreliance Identify row related to appropriate expected population deviation rate (EPDR) Identify column related to appropriate tolerable rate of deviation (TRD) Determine sample size at junction of row for EPDR and column for TRD Mod F- Major Steps in attributes Sampling: Evaluating Evaluate sample results Problem with sample rate of deviation is that it may result from a nonrepresentative sample Mod F- Upper Limit rate of deviation (ULRD) There is a (1 minus risk of overreliance) probability that the true population rate of deviation is less than or equal to the ULRD There is a (risk of overreliance) probability that the true population rate of . | Copyright © 2013 by The McGraw-Hill Companies, Inc. All rights reserved. McGraw-Hill/Irwin Module F Attributes Sampling Learning Objectives Identify the objectives of attributes sampling, define deviation conditions, and define the population for an attributes sampling application. Understand how various factors influence the size of an attributes sample. Determine the sample size for an attributes sampling application. Identify various methods of selecting an attributes sample. Evaluate the results of an attributes sampling application by determining the upper limit rate of deviation . Define sequential sampling and discovery sampling and identify when these types of sampling applications would be used. Understand how to apply nonstatistical sampling to attributes testing. Mod F- Attributes Sampling Used to estimate the extent to which a characteristic (attribute) exists within a population Used in tests of controls Mod F- Major Steps in attributes Sampling: Planning
