inst/help/Bayesian Planning.md

In koenderks/JASP-for-Audit: Audit Module for JASP

Bayesian Planning

The Bayesian planning analysis allows you to plan an audit sample without a data file using Bayesian statistics.

Default options

Population materiality:

• Absolute: Enter your population materiality as a monetary value
• Relative: Enter your population materiality as a percentage relative to the total value

Advanced options

Inherent risk and control risk:

• High: 100%
• Medium: 60%
• Low: 50%

Expected errors:

• Absolute: Enter your expected errors as a monetary value (e.g., $1.000 in a total balance of $1.000.000)
• Relative: Enter your expected errors as a percentage relative to the total size of the selection

Explanatory text:

• Enables explanatory text throughout the workflow to help you interpret the statistical results and procedure

Planning distribution:

• Beta: The beta distribution for broken taints (de Swart, Wille & Majoor, 2013)
• Beta-binomial: The finite population beta-binomial distribution for complete taints (Dyer & Pierce, 2993)

Default Output

Planning summary

• Materiality: The population materiality
• Inherent risk: Risk assessment for the inherent risk
• Control risk: Risk assessment for the control risk
• Expected errors: The number of expected errors in the selection
• Required sample size: The sample size that is required for your population statement

Tables and plots

Implied prior from risk assessments

• Produces a plot that shows the prior that is defined by the inherent risk, control risk, and the expected errors.

Expected posterior

• Adds the expected posterior to the prior graph. The expected posterior has its upper credible bound just below the materiality.

Expected Bayes factor

• Shows the expected gain of evidence when following the formulated planning.

Implicit sample

• Produces a table that displays the implicit sample on which the prior distribution is based.

Decision analysis

• Produces a plot that compares all planning distributions and their corresponding sample sizes.

References

Dyer, D., & Pierce, R. L. (1993). On the choice of the prior distribution in hypergeometric sampling. Communications in Statistics-Theory and Methods, 22(8), 2125-2146

Interdepartementaal Overlegorgaan Departementale Accountantsdiensten (2007). Handboek Auditing Rijksoverheid 2007, established by the Interdepartementaal Overlegorgaan Departementale Accountantsdiensten (IODAD) on March 28, 2006, and May 29, 2007

Swart de J, Wille J, Majoor B (2013). Het 'Push Left'-Principe als Motor van Data Analytics in de Accountantscontrole [The 'Push-Left'-Principle as a Driver of Data Analytics in Financial Audit]. Maandblad voor Accountancy en Bedrijfseconomie, 87, 425-432

koenderks/JASP-for-Audit documentation built on June 22, 2019, 2:57 a.m.