The article reviews the book "An Introduction to Corporate Accounting Standards," by W. A. Paton and A. C. Littleton.

The auditor is interested in estimating many variables in performing his/her attest function. These estimates include such items as error rates, confidence intervals, maximum overor understated amounts, and account balances. These estimates along with other collateral evidence comprise a multivariate information set upon which the auditor concludes that a set of financial statements fairly presents the financial condition and operating results of the firm. In this multivariate context, the auditor should consider the efficiency of the procedures used to estimate the parameter set upon which the decisions are made. Traditional procedures for obtaining these estimates include the maximum likelihood estimation (MLE) procedure and Bayesian approaches. Bayesian techniques require a considerable amount of judgment and training. Moreover, Stein [1955] proved that the MLE was inadmissible (could be improved upon over some portion of parameter space without worsening over the remainder of the space) as an estimator for the mean vector of a multivariate normal distribution. James and Stein [1961] and Efron and Morris [1971; 1972; 1973; 1975; 1977], among many others, generalized and extended Stein's original proof.' The result