Statistical techniques for analytical review in auditing
The technique enables the independent auditor to integrate the concepts of materiality and audit risk as set out in SAS 47 and permits effective use of sophisticated techniques without requiring a mathematics background. It is easy-to-use, includes extra math and graphics functions and can be interfaced with the Lotus 1-2-3.
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The Audit Environment
BASIC CONCEPTS OF REGRESSION ANALYSIS
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accounting adverse spread AMOUNT ESTIMATE RESIDUAL analytical review audit applications audit interface audit model audit objectives audit purpose auditor augmented matrix autocorrelation base profile calculated cm cm cm coefficient of autocorrelation coefficient of correlation coefficient of residual cost of sales cut-off point data profile degrees of freedom dependent DH&S discussed effect equation evaluation excess F ratio formula Gamma Company example heteroscedasticity homoscedastic independent variables inventory investigated kurtosis least squares linear mean method monetary precision normal distribution number of observations ordinarily overstatement pivotal element Program printout random variable recorded amount RECORDED REGRESSION regression analysis REGRESSION ESTIMATE regression function REGRESSION IMPROVEMENT REGRESSION MODEL relationship RELIABILITY FACTOR RESIDUAL VARIATION scatter diagram Section shown in Figure significant specified spread of error standard error STAR application STAR printout STAR Program statistical techniques sum of squares t-VALUE Table tests of details tions understatement XI X2 X3