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Module E

Module E. Overview of Sampling. 1. Introduction. Definition Necessary knowledge Uses of sampling in auditing. 2. Types of Sampling. Nonstatistical use judgment to select sample and/or evaluate results justification for use Statistical use random selection

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Module E

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  1. Module E Overview of Sampling Mudule E

  2. 1. Introduction • Definition • Necessary knowledge • Uses of sampling in auditing Mudule E

  3. 2. Types of Sampling • Nonstatistical • use judgment to select sample and/or evaluate results • justification for use • Statistical • use random selection • evaluate results mathematically • advantages Mudule E

  4. 3. Statistical Sampling Models • Attribute Sampling • fixed sample-size attribute sampling • discovery sampling • Variables Sampling • classical methods • MPU, ratio estimation, difference estimation • PPS Mudule E

  5. Random SelectionTechniques • Random number table • Computer generation • Systematic selection • Block sampling • Stratification Mudule E

  6. 5. Sampling Plan • Steps • Specify audit objectives and select sampling method • Define errors • Define population • Determine sample size • Select sample • Apply audit procedures • Evaluate results Mudule E

  7. 6. Sampling Risks • Terms • errors – deviations – misstatements • expected deviation rate • tolerable deviation rate • precision • reliability Mudule E

  8. 6. Sampling Risks (continued) • Nonsampling risk • Sampling risk • Risk of assessing CR too high (underreliance)Risk of incorrect rejection • Risk of assessing CR too low (overreliance)Risk of incorrect acceptance Mudule E

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  10. Attribute Sampling (Module F) Mudule E

  11. 7. Attribute Sampling • Used to estimate the extent to which a characteristic (attribute) exists within a population • Used in tests of controls • Estimate the rate at which internal control policies or procedures are not functioning as intended (deviation rate) • Compare rate to the allowable rate (tolerable deviation rate) Mudule E

  12. 7. Attribute Sampling • Example • Risk of assessing CR too low: 5% (ROO) • Tolerable deviation rate: 7% (TRD) • Expected deviation rate: 2% (EPDR) • Actual number of deviations found: 2 • Use tables on pages: 791, 792, 795 Mudule E

  13. 7. Attribute Sampling (Con’t) • Sample Size Table (5% risk) Tolerable Deviation Rate EDR 2% 3% 4% 5% 6% 7% 1.00% * * 156 93 78 66 2.00% * * * 181 127 3.00% * * * * 195 129 88 Mudule E

  14. 7. Attribute Sampling (Con’t) • Evaluation Table (5% risk) No. of deviations found n 0 1 2 3 4 5 75 4.0 6.2 8.2 10.1 11.8 13.6 80 3.7 5.8 7.7 9.5 11.1 12.7 90 3.3 5.2 6.9 8.4 9.9 11.4 7.7 Mudule E

  15. 8. Evaluate Sample Results • If UL (ULRD) > Tolerable Deviation Rate: • Conclude that internal control is not functioning effectively • Options • Increase sample size in hopes of supporting planned level of control risk • Increase level of control risk, leading to conducting more, and more effective, substantive procedures (lower detection risk) Mudule E

  16. 8. Evaluate Sample Results (Con’t) • If UL (ULRD) Tolerable Deviation Rate • Conclude that the internal control is functioning effectively • Options • Maintain planned level of control risk, leading to conducting the planned amount of substantive tests • Consider a further reduction in control risk, leading to conducting fewer substantive procedures (higher detection risk) Mudule E

  17. 9. Examples - Attribute Sampling • Case ABCDRisk of Overreliance 5% 5% 10% 10%Expected Deviation Rate 2% 4% 2% 4%Tolerable Deviation Rate 7% 9% 7% 9% Errors Found 1 2 0 2 Mudule E

  18. 10. Review Questions for Discussion • Module E E.1 E.2 E.3 E.4 E.5 E.6 E.10 E.11 E.14 E.15 E.16 E.17 Mudule E

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