25 persons trained in Multivariate Data Analysis

Twenty-five persons are now better equipped with knowledge and skills in the area of Multivariate Data Analysis, following a comprehensive training exercise hosted by the Bureau of Statistics from May 22 to June 15, 2023 at its Head office in Georgetown.

Twenty-four (24) employees from the Bureau of Statistics and one (1) employee from the Ministry of Finance participated in the capacity building exercise which ran from May 22, 2023, to June 15, 2023.

Multivariate data analysis is an approach which allows researchers and analysts to explore relationships, identify patterns, and extract meaningful information from datasets with multiple variables.

The main aim of the exercise was to provide key staff of the Bureau with the tools needed to harness the power of multivariate analysis techniques and unlock valuable insights from complex datasets.

Through a combination of theoretical concepts, hands-on exercises, and real-world case studies, participants were exposed to the necessary skills to leverage multivariate analysis for data-driven decision-making.

Participants of the training exercise now have a comprehensive understanding of multivariate data analysis techniques and their practical applications.

Among the areas covered were: Data reduction or structural simplification,

Sorting and grouping, Investigation of the dependence among variables, Prediction, Hypothesis construction and testing.

The capacity building exercise was facilitated by the Bureau’s Data Analyst Coordinator, Dr. Vincent Raja Anthonisamy who posited that “by mastering multivariate analysis techniques, staff will be able to extract valuable insights, make data-driven decisions, and drive innovation in their respective fields.”

According to Chief Statistician, Mr. Errol La Cruez, such training exercises empower participants to illustrate how invaluable data can be. He emphasized to the attendees that “through the skills you are learning and the work you are and will be doing, you will bring that value to the forefront so that people can understand how useful, valuable, and indispensable data is.”