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Presentation
Presentation
Statistics plays a pivotal role not only in data comprehension but also in modern marketing. It enables professionals in the field to understand consumer behavior better, identify market segments, assess the effectiveness of advertising campaigns, and much more. Descriptive statistics empower marketing professionals to synthesize, describe, and interpret complex information stemming from various sources, including surveys and opinion studies.
In a world where data quantities are massive, Statistics becomes an indispensable tool for rendering such voluminous information manageable, aiding in the identification of trends and the making of informed decisions. However, it is crucial to acknowledge that summarizing information inevitably entails a loss of detail.
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Class from course
Class from course
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Degree | Semesters | ECTS
Degree | Semesters | ECTS
Bachelor | Semestral | 4
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Year | Nature | Language
Year | Nature | Language
1 | Mandatory | Português
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Code
Code
ULHT168-194
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Prerequisites and corequisites
Prerequisites and corequisites
Not applicable
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Professional Internship
Professional Internship
Não
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Syllabus
Syllabus
- Course Overview: Program, Bibliography, Evaluation, Statistical Interest;
- Basic Applications in Statistics;
- Data Collection and Sampling;
- Measures of Descriptive Statistics;
- Data Organization: Graphs and Tables;
- Probabilities;
- Linear Correlation and Linear Regression.
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Objectives
Objectives
This course aims to provide exposure to crucial tools in data analysis, equipping students to apply techniques that address issues in their respective fields. The primary objectives are to endow them with the knowledge to:
- Understand the concepts of measures of central tendency, measures of dispersion, percentiles, quartiles, deciles, and measures of distribution.
- Utilize techniques of Descriptive Statistics, both numerically and graphically, to obtain appropriate interpretations of data sets.
- Gain familiarity with fundamental probability concepts and be capable of solving problems involving these concepts.
- Grasp the concept of a random variable (RV), identify whether an RV is discrete or continuous, and calculate fundamental parameters such as expected value, variance, and standard deviation based on the RV's probability function.
- Comprehend the concept of linear regression and its practical utility.
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Teaching methodologies and assessment
Teaching methodologies and assessment
Problem-Based Learning (PBL). With this approach, the program aims to engage students in purposeful learning experiences, encouraging them to tackle authentic and relevant challenges of the present. Students are prompted to apply critical thinking throughout the investigative process. This methodology fosters essential skills for both academic and professional contexts, enhancing their learning journey.
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References
References
- Agresti, A., Franklin, C. A., & Klingenberg, B. (2021). Statistics: The Art and Science of Learning from Data. 5th Edition. Global Edition.
- Bispo, R., & Maroco, J. (2005). Estatística Aplicada às Ciências Sociais e Humanas. 2a Edição. Climepsi Editores.
- Barroso, M., Sampaio, E., & Ramos, M. (2010). Exercícios de Estatística Descritiva para as Ciências Sociais. 2a Edição. Edições Silabo.
- Healey, J. F., & Donoghue, C. (2020). Statistics: A Tool for Social Research and Data Analysis. 11th Edition. Cengage Learning.
- Mazzocchi, M. (2008). Statistics for marketing and consumer research. SAGE.
- Murteira, B., Ribeiro, C. S., Silva, J. A., & Pimenta, C. (2023). Introdução à Estatística. 4a Edição. Escolar Editora.
- Reis, E., Melo, P., Andrade, R., & Calapez, T. (2021). Estatística Aplicada (volume 1). 7a Edição. Edições Sílabo.
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Office Hours
Office Hours
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Mobility
Mobility
No
