Class Applied Statistics in Social Sciences

The course aims to prepare students with necessary knowledge to: Given a data set, apply descriptive statistics techniques, both numerical and graphical, in order to obtain adequate interpretations of the data; Understand the concept of regression; Become familiar with the concepts of probability, conditional probability, and with rules for calculating with probabilities; 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; Understand the normal distribution.

Not applicable

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

Applicable

Healey, J. (2012). Statistics: A Tool for Social Research, 9th edition, Cengage Learning. 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.