Publication in the Diário da República: Aviso n.º 23177/2023 de 30/11/2023
4 ECTS; 1º Ano, Anual, 30,0 T , Cód. 66596.
Lecturer
- Cristina Maria Mendes Andrade (1)(2)
(1) Lead Professor
(2) Teaching Professor
Prerequisites
No prerequisites are required but prior knowledge of calculus and digital competencies are helpful.
Objectives
1. Understand and be able to use the key concepts of:
1.1. Descriptive statistics.
1.2. Regression and correlation
2. Analyze the data and interpret the results to make decisions.
Program
1. Descriptive Statistics
1.1. Some basic concepts.
1.2. Descriptive Statistics versus Statistical Inference.
1.3. Types of variables/data. Classification as to nature and scale. Typologies of scales.
1.4. Frequency distribution table.
1.5. Graphic representations.
1.6. Sample characteristics: measurements of location, dispersion and shape.
1.7. Diagram of extremes and quartiles. Moderate and extreme outliers.
2. Introduction to descriptive statistics in Excel and SPSS. Analysis of practical cases.
2.1. Introduction to Excel
2.2. How to build a survey in Forms
2.3. Analysis of practical cases
3. Correlation and Regression
3.1. Scatter plot. Pearson's correlation coefficient.
3.2. Interpretation of regression coefficients.
3.3. The coefficient of determination.
3.4. Correlation significance test
3.5. Analysis of practical cases in Excel.
Evaluation Methodology
Continuous assessment: Theoretical-practical assessment (020 points). Students are exempt from the examination if they obtain a grade of 10 points or higher (rounded to the nearest whole number). Students who engage in academic misconduct will be excluded from the assessment.
Assessment by examination: A written examination. Students pass the course unit if the grade obtained in this examination, rounded to the nearest whole number, is 10 points or higher.
In both assessment periods (continuous assessment and examinations), if there are doubts regarding the authenticity, authorship, or substantiation of the answers provided by a student in a written assessment, the lecturer may, before the final grades are officially published, require the student to attend a public oral examination before a panel (with a single scheduled opportunity in each assessment period) in order to verify the method, reasoning, or procedure used in arriving at the answers.
Failure to attend, refusal to cooperate, or inability to adequately justify the solutions presented may result in a revision of the grade (Final Grade = 20% WE + 80% OE) or in the written assessment being declared invalid.
Bibliography
- Marôco, J. (2014). Análise Estatística com o SPSS Statistics. (pp. 1-990). Portugal: REPORTNUMBER. ISBN: 9789899676343
- Pereira, A. e Patrício, T. (2013). SPSS Guia Prático de Utilização: Análise de dados para ciências sociais e psicologia. (Vol. 8ª Ed.). (pp. 1-256). Portugal: Edições Sílabo. ISBN: 9789726187363
- Robalo, A. (2004). Estatística: Exercícios, Vol II (Distribuições. Inferência Estatística). Lisboa: Edições Sílabo
- Siegel, A. (1988). Statistics and Data Analysis: An Introduction. New York : Wiley International Edition
Teaching Method
The theoretical lectures will be predominantly expository, making a strong interaction between theory and practical application prevail with the resolution of exercises in Excel and SPSS under the guidance of the teacher.
Software used in class
Excel and Forms
