A practical method to calculate probabilities: illustrative example from the electronic industry business

• Published in: Journal of applied statistics Vol. 44; no. 5; pp. 882 - 896
• Main Authors: Miranda, Douglas Moura, Conceição, Samuel Vieira
• Format: Journal Article
• Language: English
• Published: Abingdon Taylor & Francis 04.04.2017; Taylor & Francis Ltd
• Subjects: Applied statistics; Business; Computer programs; cumulative function; Electronics; Electronics industry; frequency table; Johnson distribution; Mathematical analysis; non-normal distribution; Normal distribution; percentiles; Probability; Probability distribution; Robustness; Statistics; Transformations
• ISSN: 0266-4763; 1360-0532
• DOI: 10.1080/02664763.2016.1189517

The real-life environment is made of probabilistic data by nature and the ability to make decisions based on probabilities is crucial in the business world. It is common to have a set of data and the need of calculating the probability of taking a value greater or less than a specific value. It is also common in many companies the unavailability of a statistical software or a specialized professional in statistics. The purpose of this paper is to present a practical and simple method to calculate probabilities from normal or non-normal distributed data set and illustrate it with an application from the electronic industry. The method does not demand statistical knowledge from the user; there is no need of normality assumptions, goodness test or transformations. The proposed method is easy to implement, robust and the experiments have evidenced its quality. The technique is validated with a large variety of instances and compared with the well-known Johnson system of distributions.