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by: Shana Koelpin DDS
Shana Koelpin DDS
GPA 3.81

K. Pollock

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K. Pollock
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This 0 page Study Guide was uploaded by Shana Koelpin DDS on Sunday November 1, 2015. The Study Guide belongs to BUS A424 at Indiana University Purdue University - Fort Wayne taught by K. Pollock in Fall. Since its upload, it has received 130 views. For similar materials see /class/233553/bus-a424-indiana-university-purdue-university-fort-wayne in Business at Indiana University Purdue University - Fort Wayne.


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Date Created: 11/01/15
A424 Chapter 17 Audit Sampling for Tests of Details of Balances I Introduction Methods for evaluating dollar misstatements ofan account balance 0 Nonstatistical use judgment 0 Statistical 0 Monetary unit sampling 0 Variable sampling ll Terminology Preparation questions 1 The amount ofmisstatement that the auditor will permit in the population and still be willing to accept the account as fairly stated is called 2 The amount by which the auditor expects the population to be misstated by before testing begins is called the misstatement in the population 3 In monetary unit sampling before the population can be considered acceptable both the and the must be between the under and over tolerable misstatement amounts 4 Assume you are using monetary unit sampling while auditing accounts receivable At yearend there are 57 accounts receivable totaling 319952 The population size is 5 Subdividing a population into two or more subpopulations is called sampling 6 Acceptable risk ofincorrect acceptance isthe risk that the auditor is willing to take of accepting a balance as correct when the true misstatement in the balance is greater than the 7 The primary factor affecting the auditor39s acceptable risk of incorrect acceptance is 8 In monetary unit sampling the sampling unit is an individual in an account balance Many terms for ending balance statistical analysis are parallel to the attribute sampling terms from Chapter 15 A Misstatement condition B Tolerable misstatement TM C Acceptable Risk of Incorrect Acceptance ARIA D Estimate of misstatement in population E Analyze misstatements VS VS VS VS VS Exception condition TER ARACR EPER Analyze exceptions Major Terminology for Monetary Unit Sampling MUS Auditor Decisions Term Definition Change to Affect on Item SS Tolerable Total misstatement the auditor will increase decrease Misstatement allow in the population Acceptable risk of Risk that the sample supports the increase decrease incorrect conclusion that the recorded account CR lt 100 acceptance balance is not materially misstated ST of T 0 either 5 or 10 when it is materially misstated false AAR High positive think okay but really AP 0 misstated Acceptable risk of Risk that the sample supports the incorrect rejection conclusion that the recorded account ARIR balance is materially misstated when it is not materially misstated false negative think misstated but really olgy Assumption of For those population items misstated decrease decrease average percent of the assumed average size of each misstatement misstatement compared to the recorded amount Ill Sample Size MUS Three Steps 1 TM Tolerable Misstatement Average misstatement assumption usually 100 that is assume sample item misstated by 100 very conservative 2 3 QOC39N Allowable percent error bound TM Rec d population value Use Table 158 Expected exception rate 0 to 1 ARIA ARACR Allowable percent error bound TER Sample size 88 frequently needs to be interpolated 88 SSLowerTER EXCESS fraction X SSLowerTER SSHigherTER See Table 173 5 if CR 100 10 if CR lt100 Example 5 ARACR 0 EPER 35 TER Sample size 99 59974 865 say 87 Example same as above except 32 TER Sample size e Do example 1714 Tolerable misstatement Ave misstmt assumption Recorded popl n value Tolerable exception rate Table 158 10 ARACR 0 EPER TER Sample Size IV Select sample using Probability Proportional to size Start Problem 1728 as an example V Analysis of Results of Procedures MUS A No Exceptions Found 1 Table 159 Precision limit in percent n is sample size nabove 39 n InterPOIated nabove nabove 39 nbelow X nbelow 39 nabove Example n 52 no exceptions 10 ARIA lnterpolated 2 Error bound Rec d popl n value X Precision limit in Compute error bound for question 1714 assuming n52 and no exceptions found in sample Error bound is 3 Decision rule Error bound lt Tolerable misstatement to accept balance m With Exceptions 0 Evaluate over and understatements separately then adjust to ease the conservatism of the methodology 0 Finally compare to tolerable misstatement 1 Compute of misstatement direction important Recorded Audited Recorded 2 Upper error bound overstatements s Order from greatest to least of X CUER X of misstatement Value across misstatement found in each additional misstatement A Adjustment 0 MLE most likely estimate Under Sum of misstatement for opposite direction X Rec d value SS 0 Adjusted bound Initial error bound MLE Under 4 Lower error bound Repeat 2 and 3 for understatements s 01 Decision Compare adjusted error bounds to tolerable misstatement Error in sample needs to be below tolerable misstatement in order to accept the balance as free from material misstatement 6 Example Do1715 Calculate amount and percent of misstatement Misstatement Rec d Value Audited Value Misstatement Misstated 1 2 3 Use 88 of 100 and ARlA of 10 Assume that for a zero misstatement rate the percent of misstatement is 100 X of misstatement misstatement The lower misstatement bound is Adjustments 0 Lower bound 0 0 Adjusted bound 0 Upper bound 0 0 Adjusted bound Conclusion Based on this calculation method the population is not acceptable as stated since the upper misstatement bound exceeds the 500000 materiality limit C What to do when a boundary is above tolerable misstatement 1 Look at other tests being done alternative BRAO procedures Segregate misstatements test separately any pervasive problem Increase sample size Adjust account balance negotiated Request client to review and correct Qualify opinion Adjust tolerable misstatement ICDU39IAOON Nonstatistical sample size See Figure 172


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