Publication in the Diário da República: Despacho n.º 428/2023 de 09/01/2023 + RA-EF/641/2011/AL04 de 22/01/2025
3 ECTS; 1º Ano, 1º Semestre, 28,0 TP + 2,0 OT , Cód. 829715.
Lecturer
- Maria Isabel Vaz Pitacas (1)(2)
(1) Lead Professor
(2) Teaching Professor
Prerequisites
Not applicable
Objectives
This module aims to provide fundamental knowledge of Mathematics and Statistics as applied to Media and Business, fostering the quantitative literacy required for the critical interpretation and use of quantitative information in academic and professional contexts.
By the end of the module, students should be able to:
1. Identify and describe the main concepts and methods used in the collection, organisation and analysis of data.
2. Apply basic techniques for calculating and processing quantitative information in communication contexts.
3. Organise, represent and interpret data using tables, graphs and appropriate descriptive statistical measures.
4. Critically analyse surveys, opinion polls, indicators and other sources of quantitative information.
5. Communicate and justify conclusions based on the analysis and interpretation of data relevant to Media and Business Communication.
Program
1. Quantitative Literacy and Information Processing
1.1. Quantitative methods in the Media and Business Communication.
1.2. Data, information and knowledge.
1.3. Ratios, proportions, percentages and indicators.
1.4. Absolute and relative changes.
1.5. Reading, interpreting and communicating quantitative information.
2. Data Representation and Visualisation
2.1. Organising data in tables.
2.2. Graphical representations: bar charts, pie charts and line graphs.
2.3. Selecting the appropriate graphical representation.
2.4. Common errors and the manipulation of information through graphics.
2.5. Critical analysis of graphs and infographics.
3. Introduction to Statistics
3.1. The statistical method and stages of a statistical study.
3.2. Population, sample and statistical unit.
3.3. Qualitative and quantitative statistical variables.
3.4. Measurement scales.
3.5. Data collection, organisation and quality.
4. Descriptive Statistics
4.1. Frequency tables.
4.2. Absolute, relative and cumulative frequencies.
4.3. Measures of central tendency: mean, median and mode.
4.4. Measures of dispersion: range, variance, standard deviation and coefficient of variation.
4.5. Interpretation and comparison of data sets.
5. Applications of Quantitative Methods to Communication
5.1. Opinion polls and surveys.
5.2. Representativeness, bias and margin of error.
5.3. Communication indicators and digital metrics.
5.4. Analysis and critical interpretation of statistical results.
5.5. Communication and presentation of quantitative results.
Evaluation Methodology
Assessment by Continuous Assessment
- Written Test: 100%
- Students pass the course unit if the mark obtained in the Written Test is equal to or higher than 9.5 points.
- Students pass the course unit and are exempt from the final examination in accordance with paragraphs 11 and 12 of Article 11 of the IPT Academic Regulations.
Assessment by Final Examination
- Written Examination: 100%
- Students pass the course unit if the final examination mark is equal to or higher than 9.5 points.
- Students pass the course unit in accordance with paragraphs 11 and 12 of Article 11 of the IPT Academic Regulations.
- The assessment methods described above also apply to working students
Bibliography
- Barroso, M. e Sampaio, E. e Ramos, M. (2025). Exercícios de Estatística Descritiva para as Ciências Sociais. Lisboa: Edições Sílabo
- Bispo, R. e Maroco, J. (2005). Estatística Aplicada às Ciências Sociais e Humanas. Lisboa: Climepsi Editores
- Cabral, J. e Campos, R. (2010). Estatística. Lisboa: Edições Profissionais Sociedade Unipessoal
- Garcia, R. e Rosa, M. e Barbosa, L. (2017). Que Número é Este? Um Guia de Literacia Estatística para Jornalistas. Lisboa: Fundação Francisco Manuel dos Santos (FFMS) / PORDATA
- Huff, D. (2023). How to Lie with Statistics. London: Penguin Books
Teaching Method
Theoretical and practical classes involving guided presentations, problem-solving, data analysis and case studies, promoting the understanding, application, interpretation and critical analysis of quantitative information in communication contexts.
Software used in class
Productivity tools and e-learning.
