Introduction to Descriptive Statistic
Áreas Científicas |
Classificação |
Área Científica |
CNAEF |
Mathematics |
Ocorrência: 2022/2023 - 1S
Ciclos de Estudo/Cursos
Sigla |
Nº de Estudantes |
Plano de Estudos |
Anos Curriculares |
Créditos UCN |
Créditos ECTS |
Horas de Contacto |
Horas Totais |
TSPCDA |
22 |
Plano de Estudos_2017_18 |
2 |
- |
3 |
- |
|
Docência - Responsabilidades
Língua de trabalho
Portuguese
Objetivos
The curricular unit contents are structured, regarding its suitability for the intended learning outcomes.
Therefore, each subject approaches fundamental theoretical concepts and practical applications by solving problems that enable students to analyze certain phenomena related to the collection, processing and analysis of data sets. It is also intended that the student develops the ability to work in a team, as well as autonomy in solving exercises.
Resultados de aprendizagem e competências
- Understand and distinguish various descriptive statistics concepts.
- Describe and apply techniques for summarizing a data set.
- Build and analyze a simple linear regression model.
Modo de trabalho
Presencial
Pré-requisitos (conhecimentos prévios) e co-requisitos (conhecimentos simultâneos)
Basic knowledge of Mathematics.
Programa
- Elementary notions.
- Classification, organization and interpretation of a data set.
- Location and dispersion measures.
- Two-dimensional distributions.
- Scatter diagram.
- Pearson's correlation coefficient.
- Linear regression model.
Bibliografia Obrigatória
Figueiredo, F; Estatística Descritiva e Probabilidades, 7ª edição, Escolar Editora, 2009
Murteira, B.; Análise Exploratória de Dados: Estatística Descritiva, Lisboa, McGraw-Hill, 1993
Reis, E.; Estatística Descritiva, 7ª Edição, Edições Sílabo, 2008
Santos, C.; Estatística Descritiva - Manual de Auto-Aprendizagem, 3ª Edição, Edições Sílabo, 2018
Silvestre, A. L.; Análise de Dados e Estatística Descritiva, Escolar Editora, 2007
Métodos de ensino e atividades de aprendizagem
Theoretical Practical classes: Theoretical exposure of the subjects followed by problems solving.
Tipo de avaliação
Distributed evaluation without final exam
Componentes de Avaliação
Designation |
Peso (%) |
Teste |
85,00 |
Trabalho escrito |
15,00 |
Total: |
100,00 |
Componentes de Ocupação
Designation |
Tempo (Horas) |
Frequência das aulas |
30,00 |
Estudo autónomo |
51,00 |
Total: |
81,00 |
Obtenção de frequência
The approval in this curricular unit can be obtained through two assessment processes: Continuous Evaluation or Exam Evaluation.
Continuous assessment
2 tests, a set of tasks regularly proposed for group/individual work and and a compulsory attendance at least 75% of the classes.
Exam Evaluation
Evaluation by final examination.
Fórmula de cálculo da classificação final
Continuous assessment
Assigning by MT the average of the tests (from zero to 20) and by MTA the average of the tasks regularly proposed (from zero to 20), the final classification CF is:
CF = 0.85×MT+0.15×MTA
- If CF is greater than or equal to 10 and less than 18, the student is approved with a final mark equal to CF, provided that the classification in any of the tests was greater or equal than 8.0 values.
- f the CF is equal to or greater than 18, the student must do an oral exam. The final grade is the average between the tests and the grade of the oral exam. If the student does not attend the oral exam, the final classification will be 17 values.
If CF is less than 10, students will be able to recover the lowest test by performing a recovery test (in the same day of the first exam), provided that one of the tests is greater or equal than 8.0 values.
Observações
Mandatory attendance: at least 75% of classes.
All information about the course, including support materials, is available on the Moodle platform.