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Mathematics for Media Studies

Scholar Year: 2020/2021 - 1S

Code: CS200014    Acronym: MCS
Scientific Fields: Matemática
Section/Department: Science and Technology

Courses

Acronym N. of students Study Plan Curricular year ECTS Contact hours Total Time
CS 40 Study Plan 4,0 48 108,0

Teaching weeks: 15

Head

TeacherResponsability
Catarina Raquel Santana Coutinho Alves DelgadoHead

Weekly workload

Hours/week T TP P PL L TC E OT OT/PL TPL O S
Type of classes

Lectures

Type Teacher Classes Hours
Contact hours Totals 1 5,20
Catarina Delgado   5,90

Teaching language

Portuguese

Intended learning outcomes (Knowledges, skills and competencies to be developed by the students)

To Identify, collect and select information critically analyzing the credibility of sources.
­To understand and apply statistical tools in the analysis and resolution of problems of reality.
­To understand and critically reflect on emerging issues in the contemporary world mobilizing statistical tools.
­To collect, process and analyze data to develop a project, scheduling steps of action in accordance with the resources
and time available.
­To interpret and critically analyze theoretical and empirical data to solve problems and make appropriate decisions
using, where appropriate, technological resources.

Syllabus

Statistics
­ General aspects
­ Sampling techniques
­ Organization and interpretation of statistical characters
­ Measures of location and dispersion
­ Distributions dimensional
­ Scattergram and contingency table
­ Coefficient of linear correlation
­ Linear regression


Demonstration of the syllabus coherence with the UC intended learning outcomes

This Curricular Unit aims to develop students’ skills as citizens and as future media professionals, related to Statistics and Probability. It is intended to ensure that students: (i) develop their mathematical knowledge in terms of concepts and processes of organization, analysis and interpretation of data and probabilities, (ii) be able to critically read and interpret studies including quantitative methodologies, to contribute to their professional development and updating and (iii) develop skills in the conception of statistical studies, with regard to data collection and to its correct interpretation, contributing to the development of an investigative attitude as a future professional.

Teaching methodologies

In this Curricular Unit we focus on the active participation of students, either in individual work or in group work. The sessions will be organized taking into account the resolution of problems and its discussion to tackle the contents of the CU and carry out activities to prepare for the design of a project.
Tutorial support consists of monitoring guiding to prepare and present a project and answer questions about the issues under study.

Demonstration of the teaching methodologies coherence with the curricular unit's intended learning outcomes

Lanned learning outcomes are located at three levels: (a) mobilize concepts of statistics and probability in problem solving, (b) provide a critical interpretation of statistical studies; (c) apply the knowledge acquired to real life situations .
Thus, the activities to be developed include: (i) reading and discussion of scientific and technical texts of different nature, (ii) exploration and critical analysis of relevant issues, (iii) search for relevant information to the deepening of the themes of this Curricular Unit, (iv) development of an investigative project involving the use of quantitative and qualitative variables

Assessment methodologies and evidences

The evaluation will take into account (i) the development of a project of statistic investigation (40%), and (ii) a written test (60%).
In order to complete the course in the form of continuous assessment it is necessary to have in the written test, a minimum of 70 points (out of 200).

Attendance system

Students with special statute, in the event that they are unable to attend classes, must negotiate with each teacher (in the first 15 days of classes) the way that will be used for their evaluation, as well as the most convenient timetable.
Students that do not meet continues assessment requirement will have a final exam.

Assement and Attendance registers

Description Type Tempo (horas) End Date
Attendance (estimated)  Classes  0
  Total: 0

Bibliography

Barroso, M., Ramos, M. & Sampaio, E. (2010). Exercícios de Estatística Descritiva para as Ciências Sociais. Lisboa: Edições Sílabo.
Dinis Pestana, D. & Velosa, S. (2010). Introdução à Probabilidade e à Estatística. Lisboa: Fundação Calouste Gulbenkian.
Elizabeth, R. (2008). Estatística Descritiva. Lisboa: Edições Sílabo.
Figueiredo, F. (2009). Estatística Descritiva e Probabilidades: Exercícios propostos e resolvidos. Lisboa: Escolar Editora.
Graça Martins, M. E. & Cerveira, A. (1999). Introdução às Probabilidades e Estatística. Lisboa: Universidade aberta.
Graça Martins, M. E., Loura, L., Mendes, F. (2010). Análise de Dados. Lisboa: Editorial do Ministério da Educação.
Graça Martins, M. E., Monteiro, C., Viana, J. P., Turkman, M. A. A. (1997). Estatística: matemática – 10.º ano de escolaridade. Lisboa: Departamento do Ensino Secundário do Ministério da Educação.
Guimarães, R., Cabral, J. (2010). Estatística. Lisboa: Editora McGraw-Hill de Portugal.
Murteira, B., Ribeiro, C. S., Silva, J. A., Pimenta, C. (2010). Introdução à Estatística. Lisboa: Escolar Editora.
Santos, C. (2010). Estatística Descritiva: Manual de Auto-aprendizagem. Lisboa: Edições Sílabo.
Santos, F. (2001). Sebenta de Matemáticas Gerais - Estatística. Lisboa: Plátano Editora.

Sites:
http://alea-estp.ine.pt/
http://www.ine.pt/portal/
www.pordata.pt

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Página gerada em: 2021-03-03 às 03:25:12