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Discusses alternative strategies which may be employed when differences arise between achieved audit‐sampling results and planned results, which means that risk levels used in ex post decision making may be different from planned levels. Contrasts a conventional strategy — which is to fix the risk of incorrect acceptance at a planned level and to ignore the risk of incorrect rejection or to accept the minimum available level of that risk which is consistent, after the fact, with the planned level of risk of incorrect acceptance — with a theoretically appealing strategy which balances both risk levels in proportion to their perceived disutility. Reports on the results of an experiment involving these two strategies, in which all subjects were auditors with statistical audit experience. Suggests that the most important statistically significant finding is that, in certain circumstances, these auditors are more willing to base audit decisions on statistical evidence after the alternative strategy is explained and available for their use.

The purpose of this paper is to provide a rigorous, statistically correct, and low‐cost way to audit sample a lender's loan portfolio, be they a microlender or other type of lender. No other paper applies this method to loan portfolios, even though it is a high demand application.

Standard techniques of audit sampling and dollar unit sampling with stratification are applied to the particular case of a microlender's portfolio. Unlike the audit sampling that almost all auditors use, no arbitrary rules of thumb are applied.

The paper finds that statistical audit sampling for a lender's loan portfolio is simple, rigorous, and inexpensive.

In audit sampling, most auditors use arbitrary rules of thumb and have no idea whether they are sampling enough items to actually be sure, with some desired level of confidence, that they have found no defects. This simple, inexpensive, and statistically rigorous technique will allow auditors who actually want to do a good job to quantify the precision of their statements in a very common application.

This paper combines several disparate threads from the statistical literature on audit sampling in a way that auditors (who are usually not statisticians) can apply them for auditing the quality of a lender's portfolio – microfinance or otherwise – which is a very common need.

Traditional approaches to risk control used for planning, executing, and evaluating substantive audit tests focus primarily on the risk of accepting a materially misstated amount (β risk) and only consider passively the risk of rejecting a correctly stated amount (α risk). This article discusses an alternative – the trade‐off approach – that formally considers both risks. Although the traditional and the trade‐off approach frequently lead to the same statistical conclusion, there are some applications in which only the trade‐off approach, can provide a statistical conclusion in support of the auditor′s assertion that a client′s balance is correctly stated. The article identifies these applications and suggests that the trade‐off approach merits further consideration.

The purpose of this paper is to expose computational methods as applied to engineering systems and evolutionary processes with randomness in external actions and inherent parameters.

In total, two approaches are distinguished that rely on solvers from deterministic algorithms. Probabilistic analysis is referred to as the approximation of the response by a Taylor series expansion about the mean input. Alternatively, stochastic simulation implies random sampling of the input and statistical evaluation of the output.

Beyond the characterization of random response, methods of reliability assessment are discussed. Concepts of design improvement are presented. Optimization for robustness diminishes the sensitivity of the system to fluctuating parameters.

Deterministic algorithms available for the primary problem are utilized for stochastic analysis by statistical Monte Carlo sampling. The computational effort for the repeated solution of the primary problem depends on the variability of the system and is usually high. Alternatively, the analytic Taylor series expansion requires extension of the primary solver to the computation of derivatives of the response with respect to the random input. The method is restricted to the computation of output mean values and variances/covariances, with the effort determined by the amount of the random input. The results of the two methods are comparable within the domain of applicability.

The present account addresses the main issues related to the presence of randomness in engineering systems and processes. They comprise the analysis of stochastic systems, reliability, design improvement, optimization and robustness against randomness of the data. The analytical Taylor approach is contrasted to the statistical Monte Carlo sampling throughout. In both cases, algorithms known from the primary, deterministic problem are the starting point of stochastic treatment. The reader benefits from the comprehensive presentation of the matter in a concise manner.

Purpose — This study proposes an optimal survey design method for multi-day and multi-period panels that maximizes the statistical power of the parameter of interest under the conditions that non-linear changes in response to a policy intervention over time can be expected.

Design/methodology/approach — The proposed method addresses balances among sample size, survey duration for each wave and frequency of observation. Higher-order polynomial changes in the parameter are also addressed, allowing us to calculate optimal sampling designs for non-linear changes in response to a given policy intervention.

Findings — One of the most important findings is that variation structure in the behaviour of interest strongly influences how surveys are designed to maximize statistical power, while the type of policy to be evaluated does not influence it so much. Empirical results done by using German Mobility Panel data indicate that not only are more data collection waves needed, but longer multi-day periods of behavioural observations per wave are needed as well, with the increase in the non-linearity of the changes in response to a policy intervention.

Originality/value — This study extends previous studies on sampling designs for travel diary survey by dealing with statistical relations between sample size, survey duration for each wave, and frequency of observation, and provides the numerical and empirical results to show how the proposed method works.

The purpose of this paper is to develop an economic statistical design based on the concepts of adjusted average time to signal (AATS) and ANF for X ¯ control chart under a Weibull shock model with multiple assignable causes.

The design used in this study is based on a multiple assignable causes cost model. The new proposed cost model is compared with the same cost and time parameters and optimal design parameters under uniform and non-uniform sampling schemes.

Numerical results indicate that the cost model with non-uniform sampling cost has a lower cost than that with uniform sampling. By using sensitivity analysis, the effect of changing fixed and variable parameters of time, cost and Weibull distribution parameters on the optimum values of design parameters and loss cost is examined and discussed.

This research adds to the body of knowledge relating to the quality control of process monitoring systems. This paper may be of particular interest to practitioners of quality systems in factories where multiple assignable causes affect the production process.

The cost functions for uniform and non-uniform sampling schemes are presented based on multiple assignable causes with AATS and ANF concepts for the first time.

This paper will detail the development of a multi-objective mathematical programming model for audit sampling of balances for accounts receivable. The nonlinear nature of the model structure will require the use of a nonlinear solution algorithm, such as the GRG or the genetic algorithm embedded in a Solver spreadsheet modeling system, to obtain appropriate results.

This paper aims to investigate how professionals such as accountants, auditors, senior civil servants and academics perceive the use of audit sampling strategies adopted by professionals to increase detection rates of frauds and corruption within the public sector in Africa. It also examines the respondents’ perceived values regarding the reasons for committing frauds, types of fraud and corruption, as well as the aspects of audit sampling strategies to tackle frauds.

This research uses non-parametric statistics and logistic regression to analyse the respondents’ opinions regarding the state of frauds and corruption in Africa (particularly in Tunisia and non-Tunisia countries), the common factors behind people committing frauds, including the types of frauds and corruption and the respondents’ opinions on the use of audit sampling strategies (non-random and random) to examine the instances of frauds and corruption.

The findings indicate that most respondents prefer to use non-probabilistic audit sampling rather than more robust sampling strategies such as random sampling and systematic random sampling to detect frauds and corruption. In addition, although there are some minor statistical differences between the countries in terms of the respondents’ perceived values on skimming fraud and on the use of audit random sampling to tackle rampant corruption in Africa, the overall findings indicate that opinions do not significantly differ between the respondents from Tunisia and other countries in terms of the types of fraud, the reasons for committing fraud and the auditing sampling strategies used to investigate the frauds.

This research serves as an analytical exploratory study to instigate further audit sampling research to combat rampant fraud and corruption in the public sector in Africa.

There are few or non-existent studies investigating the application of audit sampling strategies in Africa countries, particularly to examine the application of audit random sampling and audit non-random sampling strategies to detect fraudulent activities and corruption. Correspondingly, this research carries strategic implications for accountants and auditors to successfully detect fraudulent activities and corruption in Africa.

The purpose of this paper is to discuss the characteristics of several stochastic simulation methods applied in computation issue of structure health monitoring (SHM).

On the basis of the previous studies, this research focusses on four promising methods: transitional Markov chain Monte Carlo (TMCMC), slice sampling, slice-Metropolis-Hasting (M-H), and TMCMC-slice algorithm. The slice-M-H is the improved slice sampling algorithm, and the TMCMC-slice is the improved TMCMC algorithm. The performances of the parameters samples generated by these four algorithms are evaluated using two examples: one is the numerical example of a cantilever plate; another is the plate experiment simulating one part of the mechanical structure.

Both the numerical example and experiment show that, identification accuracy of slice-M-H is higher than that of slice sampling; and the identification accuracy of TMCMC-slice is higher than that of TMCMC. In general, the identification accuracy of the methods based on slice (slice sampling and slice-M-H) is higher than that of the methods based on TMCMC (TMCMC and TMCMC-slice).

The stochastic simulation methods evaluated in this paper are mainly two categories of representative methods: one introduces the intermediate probability density functions, and another one is the auxiliary variable approach. This paper provides important references about the stochastic simulation methods to solve the ill-conditioned computation issue, which is commonly encountered in SHM.

THE Electronic Computer Exhibition and the B.I.M. conference have provided material for serious contemplation. Sir Harold Gillett, Lord Mayor of London, opening the Exhibition suggested that we are living in the age of the second industrial revolution. There are some who share the Lord Mayor's view and others who take the whole matter in their stride. One thing is certain, we shall be able to do more—and do it more efficiently.