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Business Data Analysis

Code 14081
Year 1
Semester S2
ECTS Credits 6
Workload OT(15H)/TP(30H)
Scientific area Management
Entry requirements not applicable
Learning outcomes • Provide students with a set of concepts and statistical methods of data analysis in business sciences not addressed at the undergraduate level (1st cycle);

• Encourage the student to analyze, evaluate, and state the implications of the statistical results of variable sampling processes in the management domain and in the business sciences.

• Know and understand the application of other statistical techniques to support the development of research work.
Syllabus
1. INTRODUCTION TO DATA ANALYSIS Basic concepts of statistical inference
2. REGRESSION ANALYSIS
3. ANALYSIS OF VARIANCE - SIMPLE EXPERIENCES (1 FACTOR) COMPLETELY RANDOM
4. ANALYSIS OF THE VARIANCE WITH TWO OR MORE FACTORS
5. CONTINGENCY TABLES AND CHI-SQUARE TESTS
6. FACTORIAL ANALYSIS
7. DISCRIMINANT ANALYSIS
Main Bibliography ANÁLISE QUANTITATIVA DE DADOS

Hair, Joseph F., Bill Black, Barry Babin, Rolph E. Anderson, Ronald L. Tatham (2006) Multivariate Data Analysis, 6/e, Upper Saddle River, US: Prentice Hall,

Lisboa, João V., Augusto, Mário G. e Ferreira, Pedro L. (2012), “Estatística Aplicada à Gestão”, Vida Económica, Lisboa.

Malhotra, Naresh K. e David F. Birks (2010) Marketing Research – An Applied Approach (6th ed.), Edinburgh Gate, UK: Prentice Hall,

Marôco, J. (2011). Análise Estatística com o SPSS Statistics (5th ed.), Pero Pinheiro:

McClave, James T., Benson, P. George e Sincich, Terry (2001) Statistics for Business and Economics (8th Ed.), Upper Saddle Rive, US: Prentice Hall, ISBN: 0-13-027293-0

ANÁLISE QUALITATIVA DE DADOS

Denzin, N. K., & Lincoln, Y. S. (2005). The Sage handbook of qualitative research. Sage Publications, Inc.

Jick, T. (1979). Mixing qualitative and quantitative methods: Triangulation in action. Administrative Science Quarterly, 24(4), 602–611. Retrieved from http://www
Teaching Methodologies and Assessment Criteria Expository theoretical-practical approach: aims to provide the conceptual basis necessary to understand and interpret the various instruments of statistical analysis. Theoretical foundations will be developed from the presentation of practical examples.

Practical Approach: Exercises on the subject will be carried out, with the participation of the student being desirable through the resolution and discussion of the problems presented. All content presented in the classroom and the application sheets for each chapter of the program will be made available on the Moodle platform. The application exercises will always be solved and interpreted using the SPSS software (Statistical Program for Social Sciences) and, whenever its size allows, solved in the classroom.
Language Portuguese. Tutorial support is available in English.
Last updated on: 2024-03-21

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