In this study a novel statistical test is derived for the Coefficient of Variation (CV) under normal distributions. This is a newly derived test with value to engineering sciences in aspects of production of accurate items. The CV can measure the precision of a measuring instrument, among other applications. In order to determine instrument reliability, start by generating measures using the instrument. The CV is then calculated to determine if the measures generated by the instrument are concentrated around a central point. In use of normal distribution presumption, or approximation, applicable properties of the normal distributions lead to involvement of the chi-square and t-distributions. A CV test is then constructed, and two illustrative examples conclude the discussion.
The paper describes a simple, straightforward method to measure progress of business process optimization (BPO). The aim is to derive measures of the degree of BPO attainment in order to identify future priority focus for ensuing exercises. These measures can help to identify components of business that should be improved towards full optimization of processes in business. In an ideal case of the business containing all the components, a large business scenario is assumed. However, flexibility is permissible when changes are experienced with either some business aspects missing or new ones added. A measure of BPO progress was eventually developed based on these circumstances. A BPO measurement is described for presentation as a percentage or proportion.
Keywords: BPE, BPO, change management, measure, risk management, success factor. JEL Classification: C1, C3, C5, C6, O3
When facilitating learning, quick and small assessments can assist to detect areas that require further reinforcement and also identify students who need extra help in understanding the concepts taught. This paper demonstrates with Statistics, a difficult subject to pass at Higher Education Institution (HEI) level, that when these tests are administered at high frequencies and in large numbers, students are boosted to perform better, seemingly because there is no chance to pause learning. In addition to the higher performance shown, the students' marks were more stable when checked using the Coefficient of Variation (CV) measure. This was an indication that in the case of many assessment exercises, the higher student performances obtained were also more reliable and had a better chance to be replicated when the exercise was repeated.
The paper applies regression methods to model Business Process Optimisation (BPO) in order to derive measures for the extent of BPO achievement if efforts to optimise have already started. This will help to identify components of business that still need to be improved if full optimisation has not yet been achieved in a business. Regression methods were used to explain the tentative relationship of BPO with the variables identified as components of BPO. Two models (one with dummy coefficients and another with probabilistic coefficients) were developed. The first one was found to be unsuitable and lacked resources for further development. The second was satisfactory. A measure of BPO progress was then developed. The data used in the experiments were obtained from a private bank in South Africa. A regression model was designed and then fitted, statistically tested and found to be acceptable. Also, an estimate of the measure of BPO attainment level was developed. The study achieved its main goal, but acknowledgment is made to do more experiments with several larger data sets.
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