audit sampling pertemuan 15-16 matakuliah: a0294/audit si lanjutan tahun: 2009

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  • Audit Sampling Pertemuan 15-16Matakuliah: A0294/Audit SI Lanjutan Tahun: 2009

  • Learning OutcomesPada akhir pertemuan ini, diharapkan mahasiswa akan mampu :Memahami teknik penentuan ukuran sampleMemahami teknik pengambilan sample

  • Attribute samplingIt is a statistical method used to estimate the proportion of a characteristic in a population (absence or presence of a control)

    The auditor is normally attempting to determine the operating effectiveness of a control procedure in terms of deviations from the prescribed control

  • Attribute samplingPlanning1st - Determine the objective(s) of the test2nd - Define the control deviation conditions.3rd - Define the population4rd - Define the period covered by the test5th - Define the sampling unit.6th Define the technical parameters to determine the sample size

  • Attribute samplingSample size

    It could be determined using:Mathematic formulasStatistic tablessoftware (CAAT: ACL or IDEA)

  • Attribute samplingSelect the sample, perform the tests and evaluate the resultsSelection using:Tables of random numberssoftware (CAATS: ACL or IDEA or EXCEL)Evaluation of results using:Satistic tables Software (CAATS: ACL or IDEA or EXCEL)

  • Attribute samplingKey conceptsConfidence level, say 90%(complement of risk of incorrect acceptance: 10%)Expected deviation rate (EDR)Maximum Tolerable deviation rate (MTDR)Precision of the test (P
  • Attribute samplingConfidence level (CL) or reliability level (RL) It is a probability of the auditor being correct in his/her evaluation of the risk of control (genneraly varies from 90 to 99%) CL is 100% if all the items in the population are examined

  • Attribute samplingRisk (2 types of sampling risks):Risk of assessing control risk too low (complement of reliability or confidence level)- is the probability that the sample supports the conclusion that the controls are operating effectively when they are not (we fail to recognise unreliable controls and setting CL for operations at a lower level)

    Risk of assessing control risk too high- is the probability that the sample supports the conclusion that the controls are not operating effectively when this is not the case (this situation causes setting of CL for audit on operations at a higher level and more unnecessary audit work)

  • Attribute samplingExpected deviation rate (EDR)

    Maximum expected of deviations in the population based on last year audit or a pilot testEDR allows to define an interval of confidence for the sample identifying its precision (precision

  • Attribute sampling

    Dimenso da Amostra

    Confidence level: 95%

    EDRMTDR

    2.00%3.00%4.00%5.00%6.00%7.00%8.00%9.00%10.00%15.00%20.00%

    0.00%149(0)99(0)74(0)59(0)49(0)42(0)36(0)32(0)29(0)19(0)14(0)

    0.25%236(1)157(1)117(1)93(1)78(1)66(1)58(1)51(1)46(1)30(1)22(1)

    0.50%157(1)117(1)93(1)78(1)66(1)58(1)51(1)46(1)30(1)22(1)

    0.75%208(2)117(1)93(1)78(1)66(1)58(1)51(1)46(1)30(1)22(1)

    1.00%156(2)93(1)78(1)66(1)58(1)51(1)46(1)30(1)22(1)

    1.25%156(2)124(2)78(1)66(1)58(1)51(1)46(1)30(1)22(1)

    1.50%192(3)124(2)103(2)66(1)58(1)51(1)46(1)30(1)22(1)

    1.75%227(4)153(3)103(2)88(2)77(2)51(1)46(1)30(1)22(1)

    2.00%181(4)127(3)88(2)77(2)68(1)46(1)30(1)22(1)

    2.25%208(5)127(3)88(2)77(2)68(1)61(2)30(1)22(1)

    2.50%150(4)109(3)77(2)68(2)61(2)30(1)22(1)

    2.75%173(5)109(3)95(3)68(2)61(2)30(1)22(1)

    3.00%195(6)129(4)95(3)84(3)61(2)30(1)22(1)

    3.25%148(5)112(4)84(3)61(2)30(1)22(1)

    3.50%167(6)112(4)84(3)76(3)40(2)22(1)

    3.75%185(7)129(5)100(4)76(3)40(2)22(1)

    4.00%146(6)100(4)89(4)40(2)22(1)

    5.00%158(8)116(6)40(2)30(2)

    6.00%179(11)50(3)30(2)

    7.00%68(5)37(3)

    Fonte: Guy, D.M., Audit Sampling: na introduction, 56

    Tabela 1 Determinao da Dimenso da Amostra - Nvel de Confiana: 90%

    Taxa de erros esperadaTaxa de erros tolervel

    2.00%3.00%4.00%5.00%6.00%7.00%8.00%9.00%10.00%15.00%20.00%

    0.00%114(0)76(0)57(0)45(0)38(0)32(0)28(0)25(0)22(0)15(0)11(0)

    0.25%194(1)129(1)96(1)77(1)64(1)55(1)48(1)42(1)38(1)25(1)18(1)

    0.50%194(1)129(1)96(1)77(1)64(1)55(1)48(1)42(1)38(1)25(1)18(1)

    0.75%265(2)129(1)96(1)77(1)64(1)55(1)48(1)42(1)38(1)25(1)18(1)

    1.00%176(2)96(1)77(1)64(1)55(1)48(1)42(1)38(1)25(1)18(1)

    1.25%221(3)132(2)77(1)64(1)55(1)48(1)42(1)38(1)25(1)18(1)

    1.50%132(2)105(2)64(1)55(1)48(1)42(1)38(1)25(1)18(1)

    1.75%166(3)105(2)88(2)55(1)48(1)42(1)38(1)25(1)18(1)

    2.00%198(4)132(3)88(2)75(2)48(1)42(1)38(1)25(1)18(1)

    2.25%132(3)88(2)75(2)65(2)42(1)38(1)25(1)18(1)

    2.50%158(4)110(3)75(2)65(2)58(2)38(1)25(1)18(1)

    2.75%209(6)132(4)94(3)65(2)58(2)52(2)25(1)18(1)

    3.00%132(4)94(3)65(2)58(2)52(2)25(1)18(1)

    3.25%153(5)113(4)82(3)58(2)52(2)25(1)18(1)

    3.50%194(7)113(4)82(3)73(3)52(2)25(1)18(1)

    3.75%131(5)98(4)73(3)52(2)25(1)18(1)

    4.00%149(6)98(4)73(3)65(3)25(1)18(1)

    5.00%160(8)115(6)78(4)34(2)18(1)

    6.00%182(11)116(7)43(3)25(2)

    7.00%199(14)52(4)25(2)

    Fonte: Guy, D.M., Audit Sampling: na introduction, 55

    Limite Superior Obtido

    Tabela 2 Limite Superior Obtido: Percentagem de Erro - Nvel de Confiana: 95%

    Dimenso da amostraNmero de erros detectados

    012345678910

    2511.317.6

    309.514.919.6

    358.312.917.0

    407.311.415.018.3

    456.510.513.416.419.2

    505.99.212.114.817.419.9

    555.48.411.113.515.918.2

    604.97.710.212.514.716.818.8

    654.67.19.411.513.615.517.419.3

    704.26.68.810.812.614.516.318.019.7

    754.06.28.210.111.813.615.216.918.520.0

    803.75.87.79.511.112.714.315.917.418.9

    903.35.26.98.49.911.412.814.215.516.818.2

    1003.04.76.27.69.010.311.512.814.015.216.4

    1252.43.85.06.17.28.39.310.311.312.313.2

    1502.03.24.25.16.06.97.88.69.510.311.1

    2001.52.43.23.94.65.25.96.57.27.88.4

    Fonte: Guy, D.M., Audit Sampling: na introduction, 58

  • Attribute sampling

    Dimenso da Amostra

    Confidence level: 95%

    Expected error rateAcceptable error rate

    2.00%3.00%4.00%5.00%6.00%7.00%8.00%9.00%10.00%15.00%20.00%

    0.00%149(0)99(0)74(0)59(0)49(0)42(0)36(0)32(0)29(0)19(0)14(0)

    0.25%236(1)157(1)117(1)93(1)78(1)66(1)58(1)51(1)46(1)30(1)22(1)

    0.50%157(1)117(1)93(1)78(1)66(1)58(1)51(1)46(1)30(1)22(1)

    0.75%208(2)117(1)93(1)78(1)66(1)58(1)51(1)46(1)30(1)22(1)

    1.00%156(2)93(1)78(1)66(1)58(1)51(1)46(1)30(1)22(1)

    1.25%156(2)124(2)78(1)66(1)58(1)51(1)46(1)30(1)22(1)

    1.50%192(3)124(2)103(2)66(1)58(1)51(1)46(1)30(1)22(1)

    1.75%227(4)153(3)103(2)88(2)77(2)51(1)46(1)30(1)22(1)

    2.00%181(4)127(3)88(2)77(2)68(1)46(1)30(1)22(1)

    2.25%208(5)127(3)88(2)77(2)68(1)61(2)30(1)22(1)

    2.50%150(4)109(3)77(2)68(2)61(2)30(1)22(1)

    2.75%173(5)109(3)95(3)68(2)61(2)30(1)22(1)

    3.00%195(6)129(4)95(3)84(3)61(2)30(1)22(1)

    3.25%148(5)112(4)84(3)61(2)30(1)22(1)

    3.50%167(6)112(4)84(3)76(3)40(2)22(1)

    3.75%185(7)129(5)100(4)76(3)40(2)22(1)

    4.00%146(6)100(4)89(4)40(2)22(1)

    5.00%158(8)116(6)40(2)30(2)

    6.00%179(11)50(3)30(2)

    7.00%68(5)37(3)

    Tabela 1 Determinao da Dimenso da Amostra - Nvel de Confiana: 90%

    Taxa de erros esperadaTaxa de erros tolervel

    2.00%3.00%4.00%5.00%6.00%7.00%8.00%9.00%10.00%15.00%20.00%

    0.00%114(0)76(0)57(0)45(0)38(0)32(0)28(0)25(0)22(0)15(0)11(0)

    0.25%194(1)129(1)96(1)77(1)64(1)55(1)48(1)42(1)38(1)25(1)18(1)

    0.50%194(1)129(1)96(1)77(1)64(1)55(1)48(1)42(1)38(1)25(1)18(1)

    0.75%265(2)129(1)96(1)77(1)64(1)55(1)48(1)42(1)38(1)25(1)18(1)

    1.00%176(2)96(1)77(1)64(1)55(1)48(1)42(1)38(1)25(1)18(1)

    1.25%221(3)132(2)77(1)64(1)55(1)48(1)42(1)38(1)25(1)18(1)

    1.50%132(2)105(2)64(1)55(1)48(1)42(1)38(1)25(1)18(1)

    1.75%166(3)105(2)88(2)55(1)48(1)42(1)38(1)25(1)18(1)

    2.00%198(4)132(3)88(2)75(2)48(1)42(1)38(1)25(1)18(1)

    2.25%132(3)88(2)75(2)65(2)42(1)38(1)25(1)18(1)

    2.50%158(4)110(3)75(2)65(2)58(2)38(1)25(1)18(1)

    2.75%209(6)132(4)94(3)65(2)58(2)52(2)25(1)18(1)

    3.00%132(4)94(3)65(2)58(2)52(2)25(1)18(1)

    3.25%153(5)113(4)82(3)58(2)52(2)25(1)18(1)

    3.50%194(7)113(4)82(3)73(3)52(2)25(1)18(1)

    3.75%131(5)98(4)73(3)52(2)25(1)18(1)

    4.00%149(6)98(4)73(3)65(3)25(1)18(1)

    5.00%160(8)115(6)78(4)34(2)18(1)

    6.00%182(11)116(7)43(3)25(2)

    7.00%199(14)52(4)25(2)

    Limite Superior Obtido

    Upper error limit rate confidence level: 95%

    Sample sizeNumber of errors found

    012345678910

    2511.317.6

    309.514.919.6

    358.312.917.0

    407.311.415.018.3

    456.510.513.416.419.2

    505.99.212.114.817.419.9

    555.48.411.113.515.918.2

    604.97.710.212.514.716.818.8

    654.67.19.411.513.615.517.419.3

    704.26.68.810.812.614.516.318.019.7

    754.06.28.210.111.813.615.216.918.520.0

    803.75.87.79.511.112.714.315.917.418.9

    903.35.26.98.49.911.412.814.215.516.818.2

    1003.04.76.27.69.010.311.512.814.015.216.4

    1252.43.85.06.17.28.39.310.311.312.313.2

    1502.03.24.25.16.06.97.88.69.510.311.1

    2001.52.43.23.94.65.25.96.57.27.88.4

  • Variables samplingAuditor problem:Is there the possibility of overstatement in value of some item of the population which could result in a qualified opinion?

  • Variables sampling statistical methods

    Sampling proporcionate to size (PPS/MUS)Classical variables sampling:Direct projection (stratification required);Ratio or difference estimation (when errors are fairly frequent)

  • Monetary Unit Sampling (MUS)The classical variables sampling can fail in the detection of the material mistake because:The methods of selection are random and based on physical registers (we maynot choose a document that contains a mistake)There is a possibilit