Courses catalog
Data science and statistical analysis

Bibliometric data processing with SPSS

DESCRIPTION

In the dynamic field of scientific activity and bibliometric data analysis, the ability to process and analyse large volumes of data has become crucial. It is therefore essential to acquire skills in statistical analysis tools in order to be able to draw accurate and meaningful conclusions from the data they handle. SPSS, one of the most widely recognised software programmes for statistical analysis, is essential for those seeking to deepen their understanding of quantitative techniques and strengthen their ability to interpret and communicate results. The introductory SPSS course is designed to provide a solid grounding in database management and in performing basic and advanced statistical analyses using SPSS. The aim is to reinforce basic aspects in the selection of appropriate statistical tests for each case, from descriptive analysis to non-linear regression and analysis of categorical variables, and their correct application and interpretation.

STRUCTURE

Module 1 – Introduction to and features of the SPSS framework

  • Overview of SPSS in bibliometric analysis.
  • Exploring the working environment: interface, features and menus.
  • Importance and application of SPSS in the analysis of bibliometric data.

Module 2 – Fundamentals and basic commands in SPSS

  • Introduction to the data editor: creating, managing and importing datasets.
  • Basic commands and initial operations in SPSS.
  • Variables management and first descriptive analyses.

Module 3 – Correlations and Bivariate Analysis in SPSS

  • Key correlation concepts and their relevance to bibliometric data.
  • How to perform and interpret bivariate analysis and correlations in SPSS.
  • Specific techniques and considerations for bibliometric data.

Module 4 – Visualisation and graphical representation in SPSS

  • Visualisation tools and techniques in SPSS.
  • Creating graphs and visualisations adapted to bibliometric data.
  • Interpreting and presenting visualisations for clear communication.

Module 5 – Advanced analysis and regression in SPSS

  • Hypothesis testing and selection of appropriate tests in SPSS.
  • Linear and non-linear regressions for bibliometric data.
  • Analysis and interpretation of categorical variables in SPSS.