# Application 2: Introduction to ACL

Among those tools are software programs such as ACL. These programs can make auditing much easier, but they can beÃ‚ intimidating to first-timeÃ‚ users. This Application should make you more comfortable with ACL software and should also giveÃ‚ you a basic understanding of how auditing software works in case you use different software later in your career. Be sureÃ‚ to look at this weekâ€™s ACL tutorial before completing this Application.
Complete the ACL tutorial found in the companion website http://www.cengagebrain.com/cgiwadsworth/
course_products_wp.pl?fid=M20b&product_isbn_issn=9781133939153&token=. After completing the tutorial,Ã‚ download the ACL data file Husky Inventory 2009.xls from the Auditing companion website. Create a new project and addÃ‚ the downloaded file. In a Word document, complete the following tasks:
1.Using the Husky Inventory 2009 table: 1.Find the sample sizes using attribute sampling with a 90% confidence level, anÃ‚ Upper Error Limit of 15%, and an Expected Error Rate of 5%.
2.How many tolerable errors are there for the selected sample?
3.Describe what happens to the sample size as you do the following, keeping everything else the same as step (a):
1.Increase the confidence level to 95%
2.Increase the upper error limit to 25%
3.Increase the expected error rate to 10%
2.Find the sample size using MUS sampling with a confidence level of 90%, materiality of 500,000, and expected totalÃ‚ errors of 100,000.
3.ACL uses different terms to describe the same concept as the text. Confidence level is the inverse of sampling risk, upperÃ‚ error limit is the same as tolerable failure rate, and expected error rate is the same as expected failure rate. For MUSÃ‚ sampling, ACL calls tolerable misstatement materiality and calls expected misstatement expected total errors. Write aÃ‚ paragraph to define what confidence level, upper error limit, expected error rate, materiality, and expected total errors areÃ‚ and describe how they affect sample size.

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