Mathematic and Statistics for Social Sciences

Recommended Prerequisites

There are no prerequisites.

Teaching Methods

The lectures are simultaneously theoretical and practical which encourages students to follow the theoretical concepts using practical examples, as much as possible in the area of Sociology. During each class, after the presentation of the theoretical concepts using slides and examples solved and discussed on the board with the students, illustrative exercises are then solved. Students are encouraged to participate in classes, both in discussing examples and in solving practical exercises, aiming to stimulate their critical thinking.     

Learning Outcomes

After attending this course the student should be able to:

- Identify the main characteristics of a set, plot sets and perform operations between sets;

- Identify and characterize linear, quadratic, exponential and logarithmic functions;

- Organize data in frequency tables, as well as compute and interpret the main measurements that characterize the data, in particular measures of location, dispersion, asymmetry, kurtosis and concentration;

- Compute and interpret the existence of linear relationships between data points.    

Work Placement(s)

No

Syllabus

PART I - Mathematics

1 Set Theory

1.1 The notion of set

1.2 Subsets, universal set and set of parties

1.3 Euler-Venn diagrams

1.4 Operations on sets

1.5 Partition of a set

2 Functions

2.1 Definition

2.2 Surjective, injective and bijective functions

2.3 Inverse function

2.4 Real functions of real variable

2.5 Study and graphical representation of lines and quadratic functions

2.6 Exponential and logarithmic functions

PART II - Statistics

3 Descriptive Statistics

3.1 Distribution frequency

3.2 Measures of location

3.3 Measures of dispersion

3.4 Measures of bias and kurtosis

3.5 Measures of concentration: Lorenz Curve and Gini Index

4 Linear Regression

4.1 Diagram of dispersion

4.2 Simple linear regression model

4.3 Coefficient determination and coefficient of linear correlation.

Head Lecturer(s)

Humberto José da Silva Pereira Rocha

Assessment Methods

Assessment
Periodic or by final exam as given in the course information: 100.0%

Bibliography

Bibliografia obrigatória:

Rocha, H., Martins, R., Pascoal, R. (2021) Estatística Descritiva para as Ciências Sociais. Lisboa : Edições Sílabo.

 

Bibliografia de consulta:

Guimarães, R. C. (1999) Estatística. Lisboa : Editora McGraw-Hill de Portugal. [BP 519.2 GUI]

Murteira, B., et al. (2010) Introdução à Estatística. Lisboa : Escolar Editora. [BP 519.2 INT].