Research ArticleOpen accessIn the abstractClayboy Pottery Company: A Case Study in Quality Management in a Job Shop Operations SystemMichael R. SummersBackground: This case study is designed for upper-level undergraduate students in a basic operations management course. Prerequisites would include statistics and computer science. Objective: The purpose of the case is to give the students an opportunity to apply statistical quality control techniques. The case presents an interesting problem in a real setting and students will be forced to consider realistic … …American Journal of Economics and Business Administration, Vol. 2, Issue 1 · 31 Mar 2010 · 8,202 accessesView PDFCite
Research ArticleOpen accessIn the abstractIntervention Model for Analyzing the Impact of Terrorism to Tourism IndustryZ. Ismail, Suhartono, A. Yahaya, R. EfendiProblem statement: It is common in time series data with extreme change in its mean caused by an intervention which comes from external and/or internal factors. This extreme change in mean is known as regime change or structural change. Problems of external factor intervention such as the effect of the Arab oil embargo to consumption level of electricity in United … …Journal of Mathematics and Statistics, Vol. 5, Issue 4 · 31 Dec 2009 · 7,944 accessesView PDFCite
Research ArticleOpen accessIn the abstractCredit Market Development and Economic GrowthAthanasios Vazakidis, Antonios AdamopoulosProblem statement: This study investigated the relationship between credit market development and economic growth for Italy for the period 1965-2007 using a Vector Error Correction Model (VECM). Questions were raised whether economic growth spurs credit market development taking into account the negative effect of inflation rate on credit market development. This study aimed to investigate the short-run and the long-run … …American Journal of Economics and Business Administration, Vol. 1, Issue 1 · 31 Mar 2009 · 8,402 accessesView PDFCite
Research ArticleOpen accessIn the abstractComputational Discrete Time Markov Chain with Correlated Transition ProbabilitiesPeerayuth CharnsethikulThis study presents a computational procedure for analyzing statistics of steady state probabilities in a discrete time Markov chain with correlations among their transition probabilities. The proposed model simply uses the first order Taylor’s series expansion and statistical expected value properties to obtain the resulting linear matrix equations system. Computationally, the bottleneck is O(n4) but can be improved by distributed … …Journal of Mathematics and Statistics, Vol. 2, Issue 4 · 31 Dec 2007 · 6,648 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordModeling Positive Time Series Data: A Neglected Aspect in Time Series CoursesMaman A. Djauhari, Lee Siaw Li, Rohayu Mohd SallehSomething has been forgotten in time series courses, in particular, when dealing with positive datasets. To describe the pattern hidden in this type of datasets, before we use a sophisticated method of modeling such as Autoregressive Integrated Moving Average (ARIMA), we propose to check first whether the data represent a Geometric Brownian Motion (GBM) process. If it is affirmative, unlike … …American Journal of Applied Sciences, Vol. 13, Issue 7 · 1 Jul 2016 · 7,533 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordAn Application of Univariate Statistics to Hotelling's T2Dr. A. PolymenisProblem statement: Hotelling's T2 statistic has been well documented in the existing literature and exact as well as asymptotic results have been obtained. In the present article, we focus on an important particular case of T2 and we note that, there is no clear way to show, how univariate results, used in the theory of Student’s t statistic, could be … …Journal of Mathematics and Statistics, Vol. 7, Issue 1 · 25 Mar 2011 · 7,660 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordBayesian Statistical Inference for Number Counting ExperimentsDiego CasadeiStatistical inference describes how to infer about the true but unknown population from the measured sample and is a fundamental ingredient in scientific data analysis. Often one knows the probability model and wishes to estimate its parameters. The Bayesian approach provides a solution in terms of the posterior probability density function of the parameters of interest, given the model, the … …American Journal of Engineering and Applied Sciences, Vol. 8, Issue 4 · 27 Nov 2015 · 7,570 accessesView PDFCite