In multivariate statistical analyses, a large number of variables are involved. These methods are required to explain the relationships between these variables. In this approach, many factors that are considered as data in univariate statistical analyses are included in the system as variables in multivariate analyses.

Multivariate correspondence analysis is especially suitable for analyzing categorical data. The graphical output of the analysis can be used for decision-making and provides rich information. By visualizing the proximity of variables on a map, it presents relationships that cannot be explained in tables.

Access to the implemented dataset can be obtained from Kaggle's database and the "Basic Income" link. The data were acquired through a survey conducted by Dalia Research in 2016, targeting countries that are members of the European Union. In this survey, individuals across Europe were queried about their perspectives on the concept of "Basic Income" and whether they would vote for or against this idea if they were to cast their ballots. Basic Income is an unconditional payment made by the government to each individual, irrespective of their other sources of income or employment status. It is envisaged to replace other social security payments and is believed to be sufficiently high to meet all needs. The objective of this study is to investigate the categories in which participants supporting this system are located across all variables.Basic Income is a government-funded unconditional payment aimed to replace social security, covering essential needs. The study aims to categorize supporters based on various variables.

This research included 28 European Union member states, and the participants ranged from 14 to 65 years old, including both men and women, with a total of 9,649 respondents. According to the results obtained, one-third of the participants support this system. Additionally, it was observed that those who are not in favor of this idea include individuals with insufficient knowledge about the topic, people living in rural areas, and those with high income and education levels.