Using Computerized Audit Software to Learn Statistical Sampling: An Instructional Resource

Robert C. Richardson and Timothy J. Louwers

INTRODUCTION

Section 404 of the Sarbanes-Oxley Act (U.S. House of Representatives 2002) requires an assessment of internal control. To carry out this assessment, public accounting firms must use either non-statistical or statistical sampling. Furthermore, their sample selection will fall under the scrutiny of the Public Company Accounting Oversight Board?s (PCAOB) rigorous firm inspec- tions. Although statistical sampling requires some judgment, non-statistical sampling requires more judgment. Hitzig (2004) argues that using non-statistical sampling instead of statistical sampling could subject auditors to even greater professional and legal criticism. Nevertheless, many firms have been reluctant to embrace statistical sampling. Hitzig (2004) states that this reluctance had historically been due to three major factors: the cost of sample selection, the cost of sample evaluation, and the cost of training. The cost of sample selection and the cost of sample evaluation are virtually eliminated today by the widespread availability of software packages (Hitzig 2004). All of the Big 4 firms have at least one CAATs software package (e.g., ACL, IDEA, etc.) available. Many smaller firms often have software available (Lanza 1998; Warner 1998), although they sometimes fail to understand how to properly use the software due to a lack of training and an absence of technology ?champions.?

In addition to the argument for more objective measures found in statistical sampling, certain types like Monetary-Unit-Sampling (MUS) can result in more efficient (i.e., smaller) sample sizes. MUS has the additional feature that sampling can begin before the population is complete. Al-

though the cost of training is not insignificant, at least one of the Big 4 firms believes that the potential benefits outweigh the cost as they have increased their training emphasis on Monetary- Unit-Sampling. Furthermore, the firm is moving the training to an earlier stage in their staff?s career, indicating a desire by the firm for younger staffers to get educated in statistical sampling.

Many partners are reluctant to embrace technological changes, making college students ideal apprentices of CAATs. Students stand to have the biggest initial impact in this area. It could take a decade for a college student to catch up to the industry experience of a partner, but it could take one week to surpass some partners on CAATs knowledge. Although the focus of this tutorial is statistical sampling, CAATs can also be used in conducting fraud detection procedures, performing analytical procedures, conducting data queries, as well as performing other auditing applications. We are using ACL in this tutorial; other audit software packages are similar. In other words,

learning one software package will be helpful when using another (e.g., IDEA).

Robert C. Richardson is an Associate Professor and Timothy J. Louwers is a Professor, both at James

Madison University.

The authors gratefully acknowledge the comments of the editor, Greg Gerard, and two anonymous reviewers whose comments greatly strengthened the instructional resource.

STATISTICAL SAMPLING WITH ACL

The following tutorial is divided into three main parts. In the first part, you will be asked to load ACL and the data file that you will use. In the second part, you will be asked to determine sample sizes under a variety of assumptions using Monetary Unit Sampling (MUS). MUS is used primarily for substantive testing (i.e., testing account balances). In the third part, you will be asked to determine sample sizes under a variety of assumptions using Attribute Sampling. Attribute sampling is used primarily for controls testing. Both the MUS and Attribute Sampling techniques you will use are considered statistical sampling. This tutorial will illustrate how different factors affect sample size. In addition to becoming familiar with factors that affect sample size, you will also become familiar with ACL.

Understanding the impact that certain factors have on sample size will benefit you in three ways. First, you can plan and modify your audit approach more efficiently if you can anticipate how sample sizes might change. Second, an anticipated sample size change (e.g., an increase in sample size) might reveal an error (e.g., an input error) if the actual sample size outcome is different than anticipated. Last, sample size determinants have been tested on prior CPA exams and could be included in future exams as indicated by the sections labeled ?applications of audit sampling? and ?computer-assisted audit techniques? in the Uniform CPA Exam content specifica- tion outline for auditing.

Loading ACL and Importing the Data (Estimated Time 2 minutes)

Find the file named ?Accounts Receivable for ACL? in Blackboard and save it to your desktop.

Load ACL with the disk that accompanies your textbook.

After loading ACL, select ?File,? ?New,? and ?Project.? Type in your name under file name and click ?Save.? Click next on the Data Definition Wizard. Select Disk. Select Desktop (or wherever you saved ?Accounts Receivable for ACL?), and click on ?Accounts Receivable for ACL.? Select Open.

Click through the defaults in Wizard. They are ?PCs and all other types of computers,? ?Excel File,? and ?Sheet1.? Type in your name and click ?Save.? Click ?Finish.? If a box pops up saying ?Table ?untitled? changed, save as,? click OK.

Account # Account Name 91001 91002 91003 91004 91005 91006 91007 91008 91009 91010 91011 91012 91013 91014 91015 91016 91017 91018 91019 91020 91021 91022 91023 91024 91025 91026 91027 91028 91029 91030 91031 91032 91033 91034 91035 91036 91037 91038 91039 91040 91041 91042 91043 91044 91045 91046 91047 91048 91049 91050 91051 91052 91053 91054 91055 91056 91057 91058 91059 91060 91061 91062 91063 91064 91065 91066 91067 91068 91069 91070 91071 91072 91073 91074 91075 91076 91077 91078 91079 91080 91081 91082 91083 91084 91085 91086 91087 91088 91089 91090 91091 91092 91093 91094 91095 Amount 19217.11 81203.59 13862.62 96164.06 78001.53 33507.07 157463.59 106728.46 13619.44 12520.45 46361.01 122983.13 562.01 48726.88 35650.20 6932.60 79969.96 49119.93 0.00 92744.50 101207.16 119946.01 116666.77 79987.13 81200.72 44569.01 126252.38 155594.62 63319.44 31292.66 151178.85 85469.24 43908.18 61769.99 90366.77 84205.30 146904.95 69598.13 25735.86 59509.07 59911.97 405.52 131325.76 88830.37 108302.52 82004.97 80326.74 22853.91 138063.86 40347.47 66335.13 2766.54 45982.84 33772.95 106016.10 33507.98 41471.51 19175.35 112011.73 49776.72 118845.04 10450.75 132519.48 111508.32 81349.67 72672.26 71296.55 82899.70 21790.93 136020.24 106399.43 42131.63 46248.59 42981.53 138523.26 51647.03 142891.13 155378.80 124200.56 18991.87 144259.78 14309.96 96587.76 81200.71 63914.52 114868.69 135999.91 80081.34 147321.55 10487.16 14509.68 9839.83 120096.40 96706.69 120266.46 91096 91097 91098 91099 91100 91101 91102 91103 91104 91105 91106 91107 91108 91109 91110 91111 91112 91113 91114 91115 91116 91117 91118 91119 91120 91121 91122 91123 91124 91125 91126 91127 91128 91129 91130 91131 91132 91133 91134 91135 91136 91137 91138 91139 91140 91141 91142 91143 91144 91145 91146 91147 91148 91149 91150 91151 91152 91153 91154 91155 91156 91157 91158 91159 91160 91161 91162 91163 91164 91165 91166 91167 91168 91169 91170 91171 91172 91173 91174 91175 91176 91177 91178 91179 91180 91181 91182 91183 91184 91185 91186 91187 91188 91189 91190 91191 63719.52 68405.34 30387.34 45137.88 21608.08 9414.07 119963.10 17555.79 106346.44 79664.61 93038.59 116959.66 79075.41 148796.98 127054.58 40654.28 134509.25 90422.70 115070.60 104387.66 114455.54 234.94 119677.27 38979.83 23621.22 42366.21 70095.50 75344.45 60620.12 43817.63 98814.15 80565.14 82102.97 41440.98 82302.95 105241.19 50856.06 131014.97 45493.68 151722.28 127912.34 91054.99 144159.43 85022.46 2958.60 81788.13 32344.82 22210.67 76091.42 148495.58 81926.58 10378.76 95062.84 143419.87 139429.46 52191.05 133671.28 2636.36 91627.44 90774.56 27159.94 89657.68 12142.25 26964.97 44485.73 52921.34 80697.39 129138.68 157027.43 13913.21 64510.57 112337.72 129012.21 126311.28 148078.79 118433.58 24557.53 104924.89 11474.52 74485.16 80233.77 17787.30 2159.65 58234.02 9696.56 99476.13 4406.05 29690.04 115558.84 17297.11 105972.07 67401.69 94743.59 7685.98 45651.28 110994.93 91192 91193 91194 91195 91196 91197 91198 91199 91200 91201 91202 91203 91204 91205 91206 91207 91208 91209 91210 91211 91212 91213 91214 91215 91216 91217 91218 91219 91220 91221 91222 91223 91224 91225 91226 91227 91228 91229 91230 91231 91232 91233 91234 91235 91236 91237 91238 91239 91240 91241 91242 91243 91244 91245 91246 91247 91248 91249 91250 91251 91252 91253 91254 91255 91256 91257 91258 91259 91260 91261 91262 91263 91264 91265 91266 91267 91268 91269 91270 91271 91272 91273 91274 91275 91276 91277 91278 91279 91280 91281 91282 91283 91284 91285 91286 91287 19554.70 218.96 30669.81 69482.53 38365.79 59711.93 158328.05 6690.10 47337.60 96413.98 99166.28 108234.45 115760.20 29663.22 86082.61 113175.09 17859.79 70662.31 123984.11 70312.83 49737.84 34259.99 125636.26 23451.76 91716.87 157499.68 157439.44 58228.13 81974.32 10997.92 83321.40 84046.55 9448.41 117.84 128639.66 43876.56 132448.05 83604.86 38435.28 147906.75 21302.37 68777.00 159007.41 120024.28 97332.45 37431.48 47126.94 31075.66 104064.99 33823.24 136389.16 93847.88 29987.77 66979.69 155174.55 9510.21 38448.68 157679.43 1223.20 159235.52 15129.90 102577.36 77991.56 67420.21 65580.09 53861.35 154377.35 0.00 91606.08 22011.66 73997.62 55236.48 34518.01 11574.38 103137.10 143949.22 71188.61 105875.65 146590.65 12013.95 135832.78 74637.41 112275.66 64786.02 107608.17 20903.10 61783.35 23656.36 155192.98 110405.25 151789.40 127719.97 63836.72 1317.70 149848.10 5906.63 91288 91289 91290 91291 91292 91293 91294 91295 91296 91297 91298 91299 91300 91301 91302 91303 91304 91305 91306 91307 91308 91309 91310 91311 91312 91313 91314 91315 91316 91317 91318 91319 91320 91321 91322 91323 91324 91325 91326 91327 91328 91329 91330 91331 91332 91333 91334 91335 91336 91337 91338 91339 91340 91341 91342 91343 91344 91345 91346 91347 91348 91349 91350 91351 91352 91353 91354 91355 91356 91357 91358 91359 91360 91361 91362 91363 91364 91365 91366 91367 91368 91369 91370 91371 91372 91373 91374 91375 91376 91377 91378 91379 91380 91381 91382 91383 2884.76 79574.30 141618.01 137619.04 138507.62 91718.39 46661.48 8490.09 88829.95 146246.04 19553.16 8678.99 154533.54 23591.64 150233.95 148526.15 135954.76 45535.49 39000.00 14176.77 151573.98 146465.38 67179.03 99354.59 130985.51 143136.51 102863.85 53696.81 53004.59 80173.66 83918.16 80485.62 47280.73 89870.22 24929.52 132775.87 127310.74 13789.17 78191.09 48053.44 90416.91 116815.50 55755.06 82800.37 127979.16 152863.98 71809.04 151757.76 99178.30 1542.68 46230.56 45573.85 89406.24 9293.08 134377.58 156146.13 137358.62 12386.24 2724.42 77383.51 108463.50 2799.45 114477.34 30582.63 81999.24 93496.58 114268.65 70897.44 29826.18 130159.79 91052.77 33061.98 53853.16 73785.11 87335.86 151901.37 112525.51 143517.19 19229.02 134015.67 39223.24 29896.34 31857.49 136742.38 97728.65 90207.93 106430.82 69474.75 107116.03 9785.39 82914.23 86023.59 100660.58 12419.82 154023.09 82302.40 91384 91385 91386 91387 91388 91389 91390 91391 91392 91393 91394 91395 91396 91397 91398 91399 91400 91401 91402 91403 91404 91405 91406 91407 91408 91409 91410 91411 91412 91413 91414 91415 91416 91417 91418 91419 91420 91421 91422 91423 91424 91425 91426 91427 91428 91429 91430 91431 91432 91433 91434 91435 91436 91437 91438 91439 91440 91441 91442 91443 91444 91445 91446 91447 91448 91449 91450 91451 91452 91453 91454 91455 91456 91457 91458 91459 91460 91461 91462 91463 91464 91465 91466 91467 91468 91469 91470 91471 91472 91473 91474 91475 91476 91477 91478 91479 156723.88 0.00 117708.43 26103.35 3551.59 157696.28 111125.48 39502.42 5145.97 124718.09 85620.42 108670.09 25067.16 153226.45 112837.49 53657.51 5571.36 114639.99 115490.41 22823.97 84821.36 108757.85 156698.41 134841.03 138133.29 143040.02 42222.90 79543.44 159522.25 44795.34 72024.58 106754.81 107558.68 35230.12 109694.95 36654.56 58888.78 1151.86 51216.97 86611.50 158634.67 5676.92 27319.11 135794.28 65520.22 81500.95 141941.88 134348.51 71732.48 76882.27 67596.24 94435.32 67764.19 31737.95 103489.83 63106.56 98172.56 29385.97 7656.80 114969.69 69559.68 156948.22 41676.75 105662.75 153555.01 95059.36 31371.44 47323.91 150972.46 144826.09 157630.32 69024.69 28400.90 95630.85 159359.57 125508.48 151084.33 63191.41 12148.77 80108.65 124985.35 149070.49 102905.44 72282.72 109625.86 45002.55 114006.08 130354.44 159940.11 105931.91 102787.42 48948.37 12760.48 37743.25 139468.43 128243.03 91480 91481 91482 91483 91484 91485 91486 91487 91488 91489 91490 91491 91492 91493 91494 91495 91496 91497 91498 91499 91500 154129.74 140225.65 126316.00 104711.79 103082.65 70393.81 0.00 135679.65 25103.20 117122.64 54985.91 22591.38 49605.93 35080.68 48642.68 35948.64 1378.31 113792.92 116442.78 64536.68 859563.85 Using Computerized Audit Software to Learn Statistical Sampling Using Computerized Audit Software to Learn Statistical Sampling: An Instructional Resource Robert C. Richardson and Timothy J. Louwers INTRODUCTION Section 404 of the Sarbanes-Oxley Act (U.S. House of Representatives 2002) requires an assessment of internal control. To carry out this assessment, public accounting firms must use either non-statistical or statistical sampling. Furthermore, their sample selection will fall under the scrutiny of the Public Company Accounting Oversight Board's (PCAOB) rigorous firm inspections. Although statistical sampling requires some judgment, non-statistical sampling requires more judgment. Hitzig (2004) argues that using non-statistical sampling instead of statistical sampling could subject auditors to even greater professional and legal criticism. Nevertheless, many firms have been reluctant to embrace statistical sampling. Hitzig (2004) states that this reluctance had historically been due to three major factors: the cost of sample selection, the cost of sample evaluation, and the cost of training. The cost of sample selection and the cost of sample evaluation are virtually eliminated today by the widespread availability of software packages (Hitzig 2004). All of the Big 4 firms have at least one CAATs software package (e.g., ACL, IDEA, etc.) available. Many smaller firms often have software available (Lanza 1998; Warner 1998), although they sometimes fail to understand how to properly use the software due to a lack of training and an absence of technology \"champions.\" In addition to the argument for more objective measures found in statistical sampling, certain types like Monetary-Unit-Sampling (MUS) can result in more efficient (i.e., smaller) sample sizes. MUS has the additional feature that sampling can begin before the population is complete. Although the cost of training is not insignificant, at least one of the Big 4 firms believes that the potential benefits outweigh the cost as they have increased their training emphasis on MonetaryUnit-Sampling. Furthermore, the firm is moving the training to an earlier stage in their staff's career, indicating a desire by the firm for younger staffers to get educated in statistical sampling. Many partners are reluctant to embrace technological changes, making college students ideal apprentices of CAATs. Students stand to have the biggest initial impact in this area. It could take a decade for a college student to catch up to the industry experience of a partner, but it could take one week to surpass some partners on CAATs knowledge. Although the focus of this tutorial is statistical sampling, CAATs can also be used in conducting fraud detection procedures, performing analytical procedures, conducting data queries, as well as performing other auditing applications. We are using ACL in this tutorial; other audit software packages are similar. In other words, learning one software package will be helpful when using another (e.g., IDEA). Robert C. Richardson is an Associate Professor and Timothy J. Louwers is a Professor, both at James Madison University. The authors gratefully acknowledge the comments of the editor, Greg Gerard, and two anonymous reviewers whose comments greatly strengthened the instructional resource. Richardson and Louwers STATISTICAL SAMPLING WITH ACL The following tutorial is divided into three main parts. In the first part, you will be asked to load ACL and the data file that you will use. In the second part, you will be asked to determine sample sizes under a variety of assumptions using Monetary Unit Sampling (MUS). MUS is used primarily for substantive testing (i.e., testing account balances). In the third part, you will be asked to determine sample sizes under a variety of assumptions using Attribute Sampling. Attribute sampling is used primarily for controls testing. Both the MUS and Attribute Sampling techniques you will use are considered statistical sampling. This tutorial will illustrate how different factors affect sample size. In addition to becoming familiar with factors that affect sample size, you will also become familiar with ACL. Understanding the impact that certain factors have on sample size will benefit you in three ways. First, you can plan and modify your audit approach more efficiently if you can anticipate how sample sizes might change. Second, an anticipated sample size change (e.g., an increase in sample size) might reveal an error (e.g., an input error) if the actual sample size outcome is different than anticipated. Last, sample size determinants have been tested on prior CPA exams and could be included in future exams as indicated by the sections labeled \"applications of audit sampling\" and \"computer-assisted audit techniques\" in the Uniform CPA Exam content specification outline for auditing. Loading ACL and Importing the Data (Estimated Time 2 minutes) Find the file named \"Accounts Receivable for ACL\" in Blackboard and save it to your desktop. Load ACL with the disk that accompanies your textbook. After loading ACL, select \"File,\" \"New,\" and \"Project.\" Type in your name under file name and click \"Save.\" Click next on the Data Definition Wizard. Select Disk. Select Desktop (or wherever you saved \"Accounts Receivable for ACL\"), and click on \"Accounts Receivable for ACL.\" Select Open. Click through the defaults in Wizard. They are \"PCs and all other types of computers,\" \"Excel File,\" and \"Sheet1.\" Type in your name and click \"Save.\" Click \"Finish.\" If a box pops up saying \"Table 'untitled' changed, save as,\" click OK. Using Computerized Audit Software to Learn Statistical Sampling MUS or PPS Sampling (for Substantive Testing) Choosing customer accounts receivable for confirmation is a common task in auditing. One of the first steps you should perform on a data set is to gather some basic statistics. Step 1: The data file should already be highlighted under \"Project Navigator.\" Within the data file, highlight the \"Amount\" column by clicking on the word \"Amount.\" It should cause the entire column to be highlighted in black as pictured below. Step 2: Select the \"Analyze\" application in ACL. From the drop-down choices, select \"Statistical\" and then \"Statistics.\" Step 3: With the output provided from Step 2 above, answer the following questions: What is the book value of the population? You should calculate the total on the Excel spreadsheet of the \"amount\" column and check the calculation against the book value calculated in ACL to ensure that all of the data was imported. (Additionally, you would want to compare this total to the General Ledger to ensure that all accounts were included.) How many customer accounts are there in the accounts receivable population? How many customer accounts have zero balances? What is the largest customer balance? Step 4: Your supervisor in the field would give you the following three factors to assist you in determining your sampling plan: Tolerable misstatement (i.e., materiality) Allowable risk of incorrect acceptance Expected misstatement (i.e., expected total errors) $1,500,000.00 0.10 $200,000.00 Click on the \"Sampling\" application in ACL. From the drop-down choices, select calculate sample size and a popup box should appear as pictured below. Step 5: Make sure that \"Monetary\" is checked. This will ensure that we are calculating a sample for MUS (i.e., PPS) and not Attribute Sampling. Step 6: Input Confidence. This should always be 1 minus the risk of incorrect acceptance. For our sample, it will be 1 - 0.10 = 0.90. You should input 90 in the confidence box. Step 7: Using the information obtained in Step 3 above, input population book value in the \"Population\" box. This should be 40175738.32 without commas. Step 8: Input Materiality. This should be our tolerable misstatement of 1500000.00 without commas Step 9: Input Expected Total Errors (i.e., Expected Misstatements). This should be 200000.00 without commas. Step 10: Calculate sample size and sampling interval. Click on "Calculate" (NOT on "OK") to see the sample size of 78 and the sampling interval of $512,554.11 as revealed in the screen shot below. If you accidentally click on "OK," you will have to input all four numbers again to make any modifications (i.e., start with step 1 again). . j .... File o Edit I Data 1 I Analyze Sampling pected Error R ate(%) R esult s --------------, Calculate Sample Size 80 Int er val 6.25 002 00 3 0 04 0 05 006 0 07 00 8 00 9 010 011 01 2 013 01 4 015 01 6 017 01 8 019 0 20 021 0 22 0 23 0 24 0 25 026 027 19217.11 812 0 3.59 13862.62 961 64.06 78 001 .53 33507.0 7 157 4 63.59 1 06728.4 6 1361 9.44 12 5 2 0.4 5 46361 .01 1 22 9 83.1362.01 5 48726.88 35650.20 6 9 32.6 0 79969.96 491 19.93 0.00 927 1 44.50 01207.16 1 19 946.01 1 16666.77 79987.13 812 00.72 4 45 69.01 1 26252.38 91 0 28 Size 91 001 1555 94.62 Number of Tolera ble E rrors OK Cancel Help Initial Sample Size= 80 Expected error rate - the percentage Expl ain w hy changes i n expected error rate error rate expected in the p_opulation Changes Changes Sample Si ze From To Changes To 2% 1% 3% 1% 4% 1% 0.5% 1% caused the observed changes in sample size. Risk of Assessing Control Risk Too Low Expl ai n w hy cha nges in the risk of assessi ng Note: Be sure to change expected error rate control risk too l ow caused the observed changes in back to I % sample size. Changes Changes Sample Si ze Changes To From To 5% 10% 5% 15% 5% 5% 2.5% 1% REFERENCES Hitzig, N. B. 2004. Statistical Sampling Revisited. The CPA Journal (May): 30-35. Lanza, R. B. 1998. Take my manual audit, please. Journal of Accountancy (June): 33-36. U.S. House of Representatives. 2002. The Sarbanes-Oxley Act of 2002. Public Law 107-204 [H. R. 3763]. Washington, D.C.: Government Printing Office. Warner, P. D. 1998. ACL for Windows. The CPA Journal (November): 40-44. Account # Account Name 91001 91002 91003 91004 91005 91006 91007 91008 91009 91010 91011 91012 91013 91014 91015 91016 91017 91018 91019 91020 91021 91022 91023 91024 91025 91026 91027 91028 91029 91030 91031 91032 91033 91034 91035 91036 91037 91038 91039 91040 91041 91042 91043 91044 91045 91046 91047 91048 91049 91050 91051 91052 91053 91054 91055 91056 91057 91058 91059 91060 91061 91062 91063 91064 91065 91066 91067 91068 91069 91070 91071 91072 91073 91074 91075 91076 91077 91078 91079 91080 91081 91082 91083 91084 91085 91086 91087 91088 91089 91090 91091 91092 91093 91094 91095 Amount 19217.11 81203.59 13862.62 96164.06 78001.53 33507.07 157463.59 106728.46 13619.44 12520.45 46361.01 122983.13 562.01 48726.88 35650.20 6932.60 79969.96 49119.93 0.00 92744.50 101207.16 119946.01 116666.77 79987.13 81200.72 44569.01 126252.38 155594.62 63319.44 31292.66 151178.85 85469.24 43908.18 61769.99 90366.77 84205.30 146904.95 69598.13 25735.86 59509.07 59911.97 405.52 131325.76 88830.37 108302.52 82004.97 80326.74 22853.91 138063.86 40347.47 66335.13 2766.54 45982.84 33772.95 106016.10 33507.98 41471.51 19175.35 112011.73 49776.72 118845.04 10450.75 132519.48 111508.32 81349.67 72672.26 71296.55 82899.70 21790.93 136020.24 106399.43 42131.63 46248.59 42981.53 138523.26 51647.03 142891.13 155378.80 124200.56 18991.87 144259.78 14309.96 96587.76 81200.71 63914.52 114868.69 135999.91 80081.34 147321.55 10487.16 14509.68 9839.83 120096.40 96706.69 120266.46 91096 91097 91098 91099 91100 91101 91102 91103 91104 91105 91106 91107 91108 91109 91110 91111 91112 91113 91114 91115 91116 91117 91118 91119 91120 91121 91122 91123 91124 91125 91126 91127 91128 91129 91130 91131 91132 91133 91134 91135 91136 91137 91138 91139 91140 91141 91142 91143 91144 91145 91146 91147 91148 91149 91150 91151 91152 91153 91154 91155 91156 91157 91158 91159 91160 91161 91162 91163 91164 91165 91166 91167 91168 91169 91170 91171 91172 91173 91174 91175 91176 91177 91178 91179 91180 91181 91182 91183 91184 91185 91186 91187 91188 91189 91190 91191 63719.52 68405.34 30387.34 45137.88 21608.08 9414.07 119963.10 17555.79 106346.44 79664.61 93038.59 116959.66 79075.41 148796.98 127054.58 40654.28 134509.25 90422.70 115070.60 104387.66 114455.54 234.94 119677.27 38979.83 23621.22 42366.21 70095.50 75344.45 60620.12 43817.63 98814.15 80565.14 82102.97 41440.98 82302.95 105241.19 50856.06 131014.97 45493.68 151722.28 127912.34 91054.99 144159.43 85022.46 2958.60 81788.13 32344.82 22210.67 76091.42 148495.58 81926.58 10378.76 95062.84 143419.87 139429.46 52191.05 133671.28 2636.36 91627.44 90774.56 27159.94 89657.68 12142.25 26964.97 44485.73 52921.34 80697.39 129138.68 157027.43 13913.21 64510.57 112337.72 129012.21 126311.28 148078.79 118433.58 24557.53 104924.89 11474.52 74485.16 80233.77 17787.30 2159.65 58234.02 9696.56 99476.13 4406.05 29690.04 115558.84 17297.11 105972.07 67401.69 94743.59 7685.98 45651.28 110994.93 91192 91193 91194 91195 91196 91197 91198 91199 91200 91201 91202 91203 91204 91205 91206 91207 91208 91209 91210 91211 91212 91213 91214 91215 91216 91217 91218 91219 91220 91221 91222 91223 91224 91225 91226 91227 91228 91229 91230 91231 91232 91233 91234 91235 91236 91237 91238 91239 91240 91241 91242 91243 91244 91245 91246 91247 91248 91249 91250 91251 91252 91253 91254 91255 91256 91257 91258 91259 91260 91261 91262 91263 91264 91265 91266 91267 91268 91269 91270 91271 91272 91273 91274 91275 91276 91277 91278 91279 91280 91281 91282 91283 91284 91285 91286 91287 19554.70 218.96 30669.81 69482.53 38365.79 59711.93 158328.05 6690.10 47337.60 96413.98 99166.28 108234.45 115760.20 29663.22 86082.61 113175.09 17859.79 70662.31 123984.11 70312.83 49737.84 34259.99 125636.26 23451.76 91716.87 157499.68 157439.44 58228.13 81974.32 10997.92 83321.40 84046.55 9448.41 117.84 128639.66 43876.56 132448.05 83604.86 38435.28 147906.75 21302.37 68777.00 159007.41 120024.28 97332.45 37431.48 47126.94 31075.66 104064.99 33823.24 136389.16 93847.88 29987.77 66979.69 155174.55 9510.21 38448.68 157679.43 1223.20 159235.52 15129.90 102577.36 77991.56 67420.21 65580.09 53861.35 154377.35 0.00 91606.08 22011.66 73997.62 55236.48 34518.01 11574.38 103137.10 143949.22 71188.61 105875.65 146590.65 12013.95 135832.78 74637.41 112275.66 64786.02 107608.17 20903.10 61783.35 23656.36 155192.98 110405.25 151789.40 127719.97 63836.72 1317.70 149848.10 5906.63 91288 91289 91290 91291 91292 91293 91294 91295 91296 91297 91298 91299 91300 91301 91302 91303 91304 91305 91306 91307 91308 91309 91310 91311 91312 91313 91314 91315 91316 91317 91318 91319 91320 91321 91322 91323 91324 91325 91326 91327 91328 91329 91330 91331 91332 91333 91334 91335 91336 91337 91338 91339 91340 91341 91342 91343 91344 91345 91346 91347 91348 91349 91350 91351 91352 91353 91354 91355 91356 91357 91358 91359 91360 91361 91362 91363 91364 91365 91366 91367 91368 91369 91370 91371 91372 91373 91374 91375 91376 91377 91378 91379 91380 91381 91382 91383 2884.76 79574.30 141618.01 137619.04 138507.62 91718.39 46661.48 8490.09 88829.95 146246.04 19553.16 8678.99 154533.54 23591.64 150233.95 148526.15 135954.76 45535.49 39000.00 14176.77 151573.98 146465.38 67179.03 99354.59 130985.51 143136.51 102863.85 53696.81 53004.59 80173.66 83918.16 80485.62 47280.73 89870.22 24929.52 132775.87 127310.74 13789.17 78191.09 48053.44 90416.91 116815.50 55755.06 82800.37 127979.16 152863.98 71809.04 151757.76 99178.30 1542.68 46230.56 45573.85 89406.24 9293.08 134377.58 156146.13 137358.62 12386.24 2724.42 77383.51 108463.50 2799.45 114477.34 30582.63 81999.24 93496.58 114268.65 70897.44 29826.18 130159.79 91052.77 33061.98 53853.16 73785.11 87335.86 151901.37 112525.51 143517.19 19229.02 134015.67 39223.24 29896.34 31857.49 136742.38 97728.65 90207.93 106430.82 69474.75 107116.03 9785.39 82914.23 86023.59 100660.58 12419.82 154023.09 82302.40 91384 91385 91386 91387 91388 91389 91390 91391 91392 91393 91394 91395 91396 91397 91398 91399 91400 91401 91402 91403 91404 91405 91406 91407 91408 91409 91410 91411 91412 91413 91414 91415 91416 91417 91418 91419 91420 91421 91422 91423 91424 91425 91426 91427 91428 91429 91430 91431 91432 91433 91434 91435 91436 91437 91438 91439 91440 91441 91442 91443 91444 91445 91446 91447 91448 91449 91450 91451 91452 91453 91454 91455 91456 91457 91458 91459 91460 91461 91462 91463 91464 91465 91466 91467 91468 91469 91470 91471 91472 91473 91474 91475 91476 91477 91478 91479 156723.88 0.00 117708.43 26103.35 3551.59 157696.28 111125.48 39502.42 5145.97 124718.09 85620.42 108670.09 25067.16 153226.45 112837.49 53657.51 5571.36 114639.99 115490.41 22823.97 84821.36 108757.85 156698.41 134841.03 138133.29 143040.02 42222.90 79543.44 159522.25 44795.34 72024.58 106754.81 107558.68 35230.12 109694.95 36654.56 58888.78 1151.86 51216.97 86611.50 158634.67 5676.92 27319.11 135794.28 65520.22 81500.95 141941.88 134348.51 71732.48 76882.27 67596.24 94435.32 67764.19 31737.95 103489.83 63106.56 98172.56 29385.97 7656.80 114969.69 69559.68 156948.22 41676.75 105662.75 153555.01 95059.36 31371.44 47323.91 150972.46 144826.09 157630.32 69024.69 28400.90 95630.85 159359.57 125508.48 151084.33 63191.41 12148.77 80108.65 124985.35 149070.49 102905.44 72282.72 109625.86 45002.55 114006.08 130354.44 159940.11 105931.91 102787.42 48948.37 12760.48 37743.25 139468.43 128243.03 91480 91481 91482 91483 91484 91485 91486 91487 91488 91489 91490 91491 91492 91493 91494 91495 91496 91497 91498 91499 91500 154129.74 140225.65 126316.00 104711.79 103082.65 70393.81 0.00 135679.65 25103.20 117122.64 54985.91 22591.38 49605.93 35080.68 48642.68 35948.64 1378.31 113792.92 116442.78 64536.68 859563.85