Ateneo - UPO

The course aims to provide the necessary skills to understand and apply People and Predictive Analytics in organizational People management, with the support of dedicated software tools.

1) Agresti, A., & Finlay, B. (2020). Statistical Methods for the Social Sciences. Pearson.2) Edwards, M. R., & Edwards, K. (2019). Predictive HR Analytics: Mastering the HR Metric (2nd ed.). Kogan Page.3) Fitz-enz, J., & Mattox, J. R. (2014). Predictive Analytics for Human Resources. Wiley.Supplementary learning materials, lecture notes, and slides curated by the instructor will be available on the course e-learning platform (D.I.R.) at https://www.dir.uniupo.it.

The course learning objectives are structured across two levels:1) Methodological: acquiring knowledge of the core People and Predictive Analytics tools, with a strong emphasis on their conceptual understanding and the critical interpretation of results, promoting an informed and strategic use that goes beyond mere technical implementation.2) Computational/practical: a guided analysis of software used in empirical analysis, aimed at fully understanding the potential, limitations, and outputs of these digital solutions, rather than focusing solely on mechanical execution.

Contents of basic Statistics and of basic Mathematics in economics (see E0252, E0362 and EA007).

Classroom lectures, complemented by laboratory-based activities focused on the development of People Analytics projects, using real or realistic datasets to apply the statistical methods introduced during the course. The course also includes team-based exercises and seminars delivered by HR professionals, aimed at connecting analytical methods with real-world organizational applications.

Part of the course will be dedicated to seminars and meetings with HR professionals.

Assessment consists of three components: i)a written examination with applied exercises and data analysis problems; ii) an oral examination aimed at assessing the understanding of theoretical concepts and the appropriate use of technical terminology; iii) a People Analytics project based on the analysis of real or realistic datasets.

Introduction to People Analytics: the role of data analysis in Human Resources.Data sources and data management: information systems; data ownership and governance; data formats and introduction to databases.Data preparation: data preprocessing and feature construction; handling missing data.Exploratory data analysis and data visualization: descriptive statistics; graphical representations; construction of indicators.Data collection: basic principles of sampling; introduction to questionnaire design.Statistical models for People Analytics: multiple linear regression; logistic regression; ANOVA; exploratory clustering.

Acquisition of basic and applied statistical methods for the analysis of data in the field of People and Predictive Analytics.Development of practical skills in the use of software tools for the management, processing, and analysis of databases.Understanding of the role of People and Predictive Analytics in data-driven decision-making processes and of the contribution of analytical techniques to business processes.