Item-by-item sampling for promotional purposes

This is an accepted manuscript of an article accepted for publication by Taylor & Francis in Quality Technology & Quantitative Management on 7 June 2017, available online at doi: http://www.tandfonline.com/doi/abs/10.1080/16843703.2017.1335494In this paper we present a method for sampling items that are checked on a pass/fail basis, with a view to a statement being made about the success/failure rate for the purposes of promoting an organisation’s product/service to potential clients/customers. Attention is paid to the appropriate use of statistical phrases for the statements and this leads to the use of Bayesian credible intervals, thus it exceeds what can achieved with standard acceptance sampling techniques. The hypergeometric distribution is used to calculate successive stopping rules so that the resources used for sampling can be minimised. Extensions to the sampling procedure are considered to allow the potential for stronger and weaker statements to be made as sampling progresses. The relationship between the true error rate and the probabilities of making correct statements is discussed.Peer reviewedFinal Accepted Versio

Normal Enough? Tools to Aid Decision Making

This document is the Accepted Manuscript version of the following article: Neil H. Spencer, Margaret Lay and Lindsey Kevan de Lopez, ‘Normal enough? Tools to aid decision making’, International Journal of Social Research Methodology, Vol. 20(2): 167-179, 2017, DOI: https://doi.org/10.1080/13645579.2016.1155379. Published by Taylor & Francis.When undertaking quantitative hypothesis testing, social researchers need to decide whether the data with which they are working is suitable for parametric analyses to be used. When considering the relevant assumptions they can examine graphs and summary statistics but the decision making process is subjective and must also take into account the robustness of the proposed tests to deviations from the assumptions. We review the contemporary advice on this issue available to researchers and look back to the roots of hypothesis testing and associated work undertaken by eminent statisticians since the 1930s. From this we create a set of flow charts to give researchers tools they can use to make decisions in a more objective manner.Peer reviewedFinal Accepted Versio

Item-by-item sampling for promotional purposes

In this paper we present a method for sampling items that are checked on a pass/fail basis, with a view to a claim being made about the success/failure rate for the purposes of promoting a company’s product/service. Attention is paid to the appropriate use of statistical phrases for the claims and this leads to the development of Bayesian credible intervals. The hypergeometric distribution is used to calculate successive stopping rules so that the costs of sampling can be minimised. Extensions to the sampling procedure are considered so as to allow the potential for stronger and weaker claims to be made as sampling progresses. The relationship between the true error rate and the probabilities of making correct claims is discussed.Final Published versio