Using Applied Statistics and Multivariate Data Analysis in the Challenge to Solve Current Real-World Problems

Dear Colleagues, 

In the current knowledge society the quantity of information that is generated daily and is publicly available has increased significantly, and the ways in which we acquire, store, and treat these data are becoming more capable and powerful. As a result, it is necessary to develop methods to treat and analyze information that allow us to deal with complex problems in uncertain situations and help us to take better decisions. The most challenging problems we face are those typified as big, complex, unstructured, and whose information quality is not always ideal; usually, there is not just one solution, and a strategy is required to deal with these problems. Applied statistics, as a discipline and not only a set of tools or techniques, can provide a useful focus to address these kinds of problems, especially from a multivariate perspective. It is about using existing concepts, methods, and statistical tools in new ways to obtain new results, normally through the integration of multiple tools and often with multiple disciplines. 

The peak of data science, including the phenomenon known as big data, has placed special attention on the spectacular contributions in numerous spheres of knowledge. As a consequence, applied statistics has, to a great extent, broadened its relevance beyond the methods and tools to generate results, focusing interest on the unique nature of each problem. Applied statistics faces the challenge of solving real-world problems with statistical and mathematical tools and statistical thinking. Beyond the direct application of analysis techniques, currently, it is more effective to develop new problem solving strategies aiming to examine large and complex datasets. 

This Special Issue focuses on the new applications of multivariate statistical methods, combinations of statistical methods to address the peculiarities of specific problems and, of course, new data analysis strategies that deal with the development of complete work flows from the management of raw data to implementing efficient and easy-to-use statistical methods and the consequent communication of substantive results. 

Contributions around the following themes are particularly welcomed:

• Application of multivariate statistical methods to solve real problems;
• Sequential problem-solving strategies involving multiple statistical methods, to address modern problems in data science;
• Integration of statistical tools and methods with other different disciplines to analyze and propose tools for decision making in complex problems. 

Thank you for your contributions

Dr. José Miguel Carot Sierra
Dr. Andrea Conchado Peiró
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• Applied statistics
• Multivariate data analysis
• Statistical learning
• Big data analytics
• Mathematical optimization