Statistics and Data Analysis 2017/2018
- 5 ECTS
- Taught in Portuguese
- Both continuous and final Assessment
- relevant skillset
This course aims to provide knowledge in the field of descriptive statistics Data Analysis and Probability Theory, which allows to analyze and interpret a set of data with and without requiring the use of the SPSS
statistical software. It is intended that students can acquire the skills needed to control some statistical methods in particular to be able to:
i) Distinguish between population / sample, quantitative/qualitative variables, discrete/continuous variables
ii) Construct and interpret frequency tables and construct questionaires
iii) Build and interpret graphical representations
iv) Calculate and interpret descriptive measures
v) Build and interpret contingency tables
vi) Calculate and interpret measures of association between qualitative /quantitative variables
vii) Use IBM SPSS statistical software
viii)Interpret, analyze and use Probability Theory
Basic knowledge of mathematics
Theoretical and practical contact sessions in which predominate exhibition and demonstration components complemented with examples and practical exercises, thus seeking to stimulate debate and the understanding and participation of students in the systematic application of acquired knowledge to the proposed practical exercises; It intends to explore, as a teaching resource, using the SPSS statistical software, allowing a base contact with this tool in solving practical exercises on matters in progress and in the construction and analysis ofdigital databases.
Body of Work
1 Fundamental Concepts
1.1 Descriptive Statistics/Statistical Inference.
1.2 Population / sample; qualitative/quantitative, discrete/continuous variables;
1.3 Missing values and outliers
2 Statistical inquiries and Surveys
2.2 Questionnaires, types of questions and measurement scales
3 Frequency distributions and graphical representations
3.1 Table of frequencies
3.2 Graphical representations
4 Descriptive measures
4.1 Location: mode, median and average.
4.2 Position: quantile
4.3 Dispersion: range, variance / standard deviation, coefficient of variation.
5 Association between qualitative variables
5.1 Tables of contingency and measures of association
6. Association between quantitative variables
6.1 Diagram dispersion.
6.2 Linear correlation coefficient
6.3 Linear regression
7 Probability Theory: Random experiments; Results space; events. Algebra of events. Properties of operations with events. Conditional Probability. Bayes Theorem. Indepe
Murteira, B., Ribeiro, C. Silva, J., Andrade e Silva, J., Pimenta, C. e Pimenta, F. (2015). Introdução à estatística (3ª Edição). Escolar Editora.
Newbold, P., Carlson, W. and Thorne, B. (2013). Statistics for Business and Economics. Pearson.
Pereira, A. , Patrício, T.(2013). SPSS – Guia Prático de Utilização: Análise de Dados para Ciências Sociais e Psicologia (8ª Ed). Lisboa: Edições Sílabo.
Marôco, J. (2014). Análise estatística com o SPSS Statistics (6ª edição). ReportNumber
Afonso, A. e Nunes, C. (2011). Estatística e Probabilidades. Aplicações e soluções em SPSS. Escolar Editora.
Pestana, M. e Gageiro, J., A. (2014). SPSS – Análise de Dados para Ciências Sociais - A complementaridade do SPSS (6ª edição). Lisboa: Edições Sílabo.
Vicente, P. Reis, E. e Ferrão, F. (2001). Sondagens: a amostragem como fator decisivo de qualidade (2ª Ed.). Edições Sílabo.
Hill, M. e Hill, A. (2008). Investigação por questionário. Edições Sílabo.
Week 1- Fundamental Concepts
Week 2- Statistical inquiries and Surveys; Questionnaires, types of questions and measurement scales
Week 3- Frequency distributions and graphical representations
Week 4 Descriptive measures of location and order
Week 5- Boxplots; Descriptive measures of dispersion
Week 6- Association between quantitative variables
Week 7- Association between quantitative variables (continued). Linear Regression
Week 8- First test; Introducyion to SPSS software
Week 9- Classes with SPSS software: menus, buttons, windows and basic operations; construction and interpretation frequency tables
Week 10- Classes with SPSS: obtaining and interpreting descriptive measures; obtaining graphical representations; missing values and outliers
Week 11- Classes with SPSS: association between quantitative variables
Week 12- Association between qualitative variables: Tables of contingency and measures of association
Week 13- Classe with SPSS: association between qualitative variables
Week 14- Probability theory: Random experiments; Results space; events. Algebra of events.
Week 15 - Probability theory: properties of operations with events. Frequentist definition, Classical and Probability Axiomatic. Conditional Probability. Bayes Theorem. Independent events(fundamental theorems).
Demonstration of the syllabus coherence with the curricular unit's objectives
The syllabus taught in this course al low students to acquire training in probability and statistics. Statistics and
probability tools discussed in this course are essential for students to be able to make a correct analysis and
interpretation of data, providing them with the most appropriate tools for decision taking.
Objective (i) is achieved with items 1 and 2 of the programmatic content. Objectives (ii), (iii) and (iv) are achieved under points 3 and 4. For objectives (v) and (vi) they are achieved under points 5 and 6 of the programmatic content. Objective viii) is reached with point 7. Finally, objective vii) is achieved with the use of the SPSS software in conjunction with the teaching of points 3, 4, 5 and 6 of the programmatic contents.
Demonstration of the teaching methodologies coherence with the curricular unit's objectives
The combination between the theoretical and practical classes, student participation in group work, examples of presentation and resolution of practical exercises (algebrically and computationally) on the treated materials,
allows students to acquaint themselves with the statistical/probabilistic methods and with the real problems that they may encounter. The use of a statistical software in the classroom, and in particular SPSS, allows students to develop skills in construction and analysis of digital databases. The evaluation system adopted in the course, by promoting the analysis and discussion of problems in class and by enhancing research and working in groups, increases the capacity of analysis and reasoning of the students.
|relevant generic skill||improved?||assessed?|
|Achieving practical application of theoretical knowledge||Yes||Yes|
|Adapting to new situations|
|Analytical and synthetic skills||Yes||Yes|
|Balanced decision making||Yes||Yes|
|Commitment to effectiveness||Yes||Yes|
|Commitment to quality||Yes||Yes|
|Ethical and responsible behaviour|
|Event organization, planning and management||Yes||Yes|
|Foreign language proficiency|
|Information and learning management||Yes||Yes|
|Initiative and entrepreneurship capability||Yes||Yes|
|IT and technology proficiency||Yes||Yes|
|Problem Analysis and Assessment||Yes||Yes|
|Written and verbal communications skills||Yes||Yes|