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Statistics and Data Analysis 2017/2018

  • 5 ECTS
  • Taught in Portuguese
  • Both continuous and final Assessment

Objectives

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

Recommended Prerequisites

Basic knowledge of mathematics

Teaching Metodology

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 
2.1 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

Recommended Bibliography

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.

Complementary Bibliography

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.

Weekly Planning

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 skillimproved?assessed?
Achieving practical application of theoretical knowledgeYesYes
Adapting to new situations  
Analytical and synthetic skillsYesYes
Balanced decision makingYesYes
Commitment to effectivenessYesYes
Commitment to qualityYesYes
CreativityYesYes
Ethical and responsible behaviour  
Event organization, planning and managementYesYes
Foreign language proficiency  
Information and learning managementYesYes
Initiative and entrepreneurship capabilityYesYes
IT and technology proficiencyYesYes
Leadership  
Problem Analysis and AssessmentYesYes
Problem-solvingYesYes
Research skillsYesYes
Self-assessmentYes 
TeamworkYesYes
Written and verbal communications skillsYesYes
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