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Sridhar Mahankali

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About Sridhar Mahankali

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Profile Information

  • Name
    Sridhar Mahankali
  • Company
    Bank of America
  • Designation
    Vice President - Transformation, Robotics and Analytics
  1. I am in the process of creating an automated audit tool that does audit of System Information based on some set parameters. This involves three aspects - firstly identifying the exception in the populaton (for instance instead of a receipt, we have a payment), then calculating the sample size and then investigation of exceptions. The current sample size calculation based on Normal distribution (like most other sampling calculators) and it is based on the assumption of central limit theorom. However, the base data under question may not be a normal distribution. The challenge in that case is that we may be incorrect in our sample size calculation which may make our sample non-representative or make it much larger causing inefficiency(we are not staffed to deal with the substantially larger samples). Is there a method through which I could adapt the calculation to the underlying distribution in an automated manner?
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