The thesis deals with the issue of employees' satisfaction with individual areas of their work. The theoretical part describes the reasons for opinion ascertaining and factors influencing employee satisfaction and motivation. There are also listed the methods of employee satisfaction surveys and the approaches to statistical analysis of data from questionnaire surveys. The practical part is focused on the social climate analysis in the specific manufacturing company in areas such as remuneration, communication, work organization, teamwork, career growth, learning and development and other. The data analysis is based on categorial data analysis including detection of dependence in between individual answers and classification of employees, mainly by sex, age, department and position. For each area, there is a recommendation for the company management.

Orientador: Selene Maria Coelho Loibel / Resumo: Esta dissertação tem como foco a análise de dados categóricos, uma parte integrante da Análise Multivariada que interpreta a informação que está contida em dados discretos provenientes de contagens de eventos, possuindo características de nidas pela combinação das categorias de duas ou mais variáveis. A análise de dados categóricos é de grande importância dentro da Estatística pois tem aplicabilidade em variadas áreas do conhecimento. Os dados utilizados, foram coletados através de um question ário aplicado aos alunos de cinco Escolas Técnicas Estaduais (Etec) que nalizaram os cursos técnicos em 2018 e 2019. A pesquisa teve como objetivo obter dados locais e analisar se os alunos pretendem trabalhar ou continuar estudando na mesma área do curso que estão concluindo, se os alunos estão satisfeitos com os cursos que estão fazendo, se pretendem voltar para Etec e fazer outro curso complementar, entre outros questionamentos. Devido à natureza dos dados obtidos, as técnicas de análise de dados categóricos são adequadas e devem ser aplicadas para modelar e fazer inferências sobre os aspectos de interesse. Esta análise pode levar a resultados que serão de grande utilidade para essas Etecs. / Abstract: This dissertation focuses on the Categorical Data Analysis, an integral part of the Multivariate Analysis, which interprets embedded information in discrete data resulting from event counts, having characteristics de ned by combinations of categories from two or more variables. The categorical data analysis is of considerable importance within Statistics since it has a wide applicability in several areas of knowledge. The data set used was collected through a questionnaire applied to students from ve Public Technical Schools (Etec) that nished the technical courses in 2018 and 2019. The research aims to gather local data and analyze whether students intend to work or continue studying in the same eld of the technical course they are completing, whether students are satis ed with the courses they are attending, whether they want to go back to Etec and take another complementary course, among other questions. Due to the nature of the data obtained, categorized data analysis techniques are adequate and should be applied to model and make inferences about the aspects of interest. This analysis can be leaded to outcomes that will be very useful to these Etecs. / Mestre