Open Journal of Statistics, 2016, 6, 555-564 Published Online August 2016 in SciRes. http://www.scirp.org/journal/ojs http://dx.doi.org/10.4236/ojs.2016.64047 How to cite this paper: Sanz-Fernández, V., Cabrera, R., Muñoz-Lechuga, R., Sánchez-Navas, A. and Czerwinski, I.A. (2016) Development of a Modelling Script of Time Series Suitable for Data Mining. Open Journal of Statistics, 6, 555-564. http://dx.doi.org/10.4236/ojs.2016.64047 Development of a Modelling Script of Time Series Suitable for Data Mining Víctor Sanz-Fernández 1 , Remedios Cabrera 1* , Rubén Muñoz-Lechuga 1 , Antonio Sánchez-Navas 2 , Ivone A. Czerwinski 1 1 Departamento de Biología, Facultad de Ciencias del Mar y Ambientales, Universidad de Cádiz, Campus de Excelencia Internacional del Mar (CEIMAR), Puerto Real, Cádiz, Spain 2 Departamento de Estadística e Investigación Operativa, Facultad de Ciencias, Universidad de Cádiz, Puerto Real, Cádiz, Spain Received 30 May 2016; accepted 19 July 2016; published 22 July 2016 Copyright © 2016 by authors and Scientific Research Publishing Inc. This work is licensed under the Creative Commons Attribution International License (CC BY). http://creativecommons.org/licenses/by/4.0/ Abstract Data Mining has become an important technique for the exploration and extraction of data in nu- merous and various research projects in different fields (technology, information technology, business, the environment, economics, etc.). In the context of the analysis and visualisation of large amounts of data extracted using Data Mining on a temporary basis (time-series), free soft- ware such as R has appeared in the international context as a perfect inexpensive and efficient tool of exploitation and visualisation of time series. This has allowed the development of models, which help to extract the most relevant information from large volumes of data. In this regard, a script has been developed with the goal of implementing ARIMA models, showing these as useful and quick mechanisms for the extraction, analysis and visualisation of large data volumes, in ad- dition to presenting the great advantage of being applied in multiple branches of knowledge from economy, demography, physics, mathematics and fisheries among others. Therefore, ARIMA mod- els appear as a Data Mining technique, offering reliable, robust and high-quality results, to help validate and sustain the research carried out. Keywords Data Mining, ARIMA Models, Time Series, Script, R 1. Literature review During the last few years and due to the numerous advances in information systems, the use of means designed for * Corresponding author.