Applied Statistics in Social Sciences

Presentation

The course aims to prepare students with necessary knowledge to:

1. Given a data set, apply descriptive statistics techniques, both numerical and graphical, in order to obtain adequate interpretations of the data;
2. Understand the concept of regression;
3. Become familiar with the concepts of probability, conditional probability, and with rules for calculating with probabilities;
4. Understand the concept of random variable; identify whether a random variable is discrete or continuous; regarding probability function, be able to calculate fundamental parameters such as expected value, variance and standard deviation;
5. Understand the normal distribution.

Part of this Programme

Human Resources Management

Level of Qualification|Semesters|ECTS

| Semestral | 6

Year | Type of course unit | Language

2 |Mandatory |Português

Code

ULHT38-7136

Recommended complementary curricular units

Not applicable.

Prerequisites and co-requisites

n/a

Professional Internship

Não

Syllabus

1. Descriptive Statistics
   • Basic concepts
   • Classification of variables
   • Frequency distributions and graphical represention
   • Measures of location: Mean, mode, median and quartiles 
   • Measures of dispersion 
2. Simple Linear Regression
   • Representation of bivariate data
   • The linear correlation coefficient
   • Linear regression model.
3. Introduction to Probability Theory
   • Fundamental concepts
   • Event algebra
   • Basic probability rules and axioms
   • Conditional probability
4. Random Variables
   • Basic concepts
   • Classification of random variables.
   • Probability function. Expected value and variance.
5. Normal Distribution

Objectives

The knowledge, skills and competences to be acquired are closely related to the objectives described in the previous point. Thus, for example, the students should have the ability to apply the acquired knowledge for solving practical problems using the appropriate descriptive statistics techniques, either numerically or graphically, in order to obtain appropriate interpretations of the data set.

Teaching methodologies and assessment

The lectures are in a theoretical-practical regime, as such for each theme the necessary prerequisites for their comprehension are given first, then the fundamental concepts, and finally examples and exercises are presented.  The continuous evaluation consists of two components: the assement of participation in classe and of any proposed homework (15% of the final grade); two written tests with equal weighting, totaling 85% of the final grade.

References

• Healey, J. (2012). Statistics: A Tool for Social Research, 9th edition, Cengage Learning.
• Murteira, B.; Ribeiro, C. S.; Silva, J.A.; Pimenta, F. e Pimenta, C. (2015).  Introdução à Estatística. Escolar Editora. Lisboa. ISBN: 9789725924686
• Murteira, B. (1993). Análise Exploratória de Dados. McGraw-Hill.
• Reis, E.; Andrade, M.; Calapez, T.; Melo, P. (2015). Estatística aplicada, volume 1. Edições Sílabo. Lisboa. 2007 ISBN 978-972-618-469-0
• Reis, E.; Andrade, M.; Calapez, T.; Melo, P. (2012). Exercícios de Estatística aplicada, volume 1.  Edições Sílabo. Lisboa. ISBN 978-972-618-688-5
• Reis, E. (2009). Estatística Descritiva. Edições Sílabo. Lisboa.

Office Hours