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Statistics for Social Sciences

Code 13123
Year 1
Semester S2
ECTS Credits 5
Workload TP(45H)
Scientific area Mathematics
Entry requirements Notions of Descriptive Statistics
Mode of delivery Face-to-face.
Learning outcomes The student should be able to obtain a sample to carry out a project, describe the sample data, summarize the information by presenting it through graphs or numerical quantities. S/He will also be able to calculate probabilities. The student will be able to use the SPSS statistical package to conduct descriptive data analysis.
At the end of the course, the student should be able to:
- Understand and apply statistical methods used in the analysis of different types of data.
- Use computer programs to allow the statistical analysis of real data.
- Produce and organize the results of a statistical analysis of real data.
- Analyze and critique studies and/or articles in the area of Sociology, which are in accordance with the programmatic contents.
Syllabus - Basics of Statistics
Distinction between population and sample
Sampling
Classification of variables and their measurement scales

- Inputting data into SPSS

-Frequency tables
Frequency tables of one-dimensional variables
Contingency table for two-dimensional variables
graphical representations

- Descriptive Measures
location measures
dispersion measures
Asymmetry and flatness measurements
Linear correlation
Scatter diagram
Pearson's Correlation Coefficient

-Brief introduction to Probability Theory
Algebra of events; properties
Definition of probability. Axioms. Laplace's Law
conditional probability
Independence

-Random variables (discrete and continuous)
distribution function
Probability function and probability density
Expected value of a random variable
Variance of a random variable

- Binomial Distribution
-Normal Distribution
Throughout the semester, the different subjects will be illustrated with the SPSS statistical software.
Main Bibliography -Ferreira, Sandra S. (2022). Apontamentos de Análise de Dados Quantitativos. Departamento de Matemática, UBI.
-Maroco, J. (2007), Análise Estatística com a utilização do SPSS, Edições Silabo.
-Murteira, B., Ribeiro, C., Silva, J. e Pimenta, C. (2015), Introdução à Estatística – 3ª edição. Escolar Editora.
-Santos, C. (2010), Estatística Descritiva: Manual de autoaprendizagem - 2ª ed., Ed. Silabo.

Teaching Methodologies and Assessment Criteria 1st Test 7 values
2nd Test 7 values
Work 6 June 6 values

- A student has frequency and can go to the exam if he has at least 6 values in the EA, that is, in the sum of test 1 + test 2 + work;
- A student is exempt from the final exam if the sum of the two tests plus the work in the EA is equal to or greater than 9.5 values and has a minimum attendance of 30 hours.

- Students who obtain a classification greater than 17 values must submit to a supplementary test. In this test, the classification can be maintained or reduced, depending on the student's performance. If you do not attend, the minimum classification of 17 values will be ensured.
Language Portuguese. Tutorial support is available in English.
Last updated on: 2022-06-16

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