Year 2010-11
Data Analysis (21291)
Qualification: Degree in Political and Administration Sciences
Year: 1st
Term: 3rd
Number of ECTS credits: 4 credits
Hours of student dedication: 100
1. Introduction to the course
Descriptive statistics is a fundamental tool in the analysis of political and social reality. It allows us to compress and present large amounts of data, be it through numeric measurements or graphically, in order to observe its structure and main characteristics.
We use univariate descriptive statistics to summarise, in a useful way, the main information contained in data. For example, unemployment figures or voting percentages for each political party are indicators that provide information on the situation or actions of millions of people. Bivariate descriptive statistics allows us to analyse the relationship between two variables. For example, it allows us to examine whether unemployment affects males and females equally, or whether young people and old people vote for different parties. Statistical data is used as basic information to make all types of decisions not only in our everyday life, but also in the business, political and administration sectors. In this course students will learn to understand and use descriptive statistical tools that are constantly applied to data and typical cases in the social sciences.
2. Competencies to be achieved
Generic competences:
- Basic computing skills
- Ability to manage information (ability to search for and analyse information from various sources)
- Problem solving
- Research skills
Specific competences:
- Identify political and social methods and research techniques. Capacity to propose the study of political phenomena, design techniques for data collection and verification of hypothesis.
- Work with quantitative research data. Fluency use of quantitative data tools to apply them in a research process.
3. Contents
The aim of this course is to provide the basis from which to interpret and analyse political and social problems using data. Students will familiarise themselves with basic descriptive statistics vocabulary and learn to use analytical tools and to present data graphically. Students will also learn the basic use of SPSS, a software programme for statistical analysis.
In the previous two terms, students will have already studied how to construct and interpret social indicators, functions and other mathematical tools. Based on this knowledge, students will learn the basic principles of univariate and bivariate descriptive statistics. With respect to the different ways to present main data trends, measurements and parameters of dispersion and association, students will examine what each one is useful for, how to calculate them, how to choose the most appropriate ones based on our aim and the characteristics of the data, and how to present such information graphically.
4. Assessment
The course assessment has three parts:
- Continuous assessment which will consist of the marks obtained for the reports on the practical exercices carried out using SPSS in the seminar sessions. They will count for 30% of the final mark.
- Continuous assessment based on the exercises and problems set on the topics addressed in the theoretical sessions. This will count for 20% of the final mark.
- Final assessment by way of an exam. It will count for 50% of the final mark.
In addition, students have the opportunity to solve and self correct optional exercises and problems to consolidate their knowledge.
5. Readings and resources
5.1. Basic reading
1. Statistics
Gonick, Larry and Woollcott Smith. 2002. La estadística en cómic. Barcelona: Zendrera
Zariquey.
Moore, David S. 2000. Estadística Aplicada Bàsica. Barcelona: Antoni Bosch.
Ritchey, Ferris J. 2002. Estadística para las Ciencias Sociales. Mexico: McGraw-Hill.
2. Data analysis using SPSS
Filgueira López, Esther. 2001. Análisis de Datos con SPSSWIN. Madrid: Alianza
Editorial.
Pardo, Antonio and Miguel Ángel Ruiz. 2002. SPSS 11. Guía para el análisis de datos.
Madrid: McGraw-Hill.
SPSS INC. 2001. Guía para el análisis de datos. Madrid: SPSS Hispanoportuguesa.
(CD-Rom)
5.2. Educational resources
Students will be able to find many useful resources in the library website:
http://www.upf.edu/bibtic/ccpp/sociologia/metstat.html
6. Methodology
Large group class room based sessions: lectures where the teacher, using presentations, will explain the contents and procedures. Graphic and audiovisual support material and classroom based activities will be used.
Practical sessions: they will take place in a computer room. Here, students will work with a statistical program and will follow guided activities in small group using SPSS. For each session, students will have to present and justify their results obtained in a report.
Tutorial sessions: to solve any doubts
Work outside the classroom: autonomous study, resolving problems and exercises and correcting them and completing the reports for the practical sessions.
7. Programme of activities
Week 1: Introduction to the course and introductory contents
Week 2: Lesson on exploring data and measurements of key tendencies. Classroom based activity.
Week 3: Lesson on distribution and position measurements. Classroom based activity.
Week 2 and 3: (there are 4 seminar groups): practical activity on exploring data using SPSS in a computer room. Report due in at the end of the session.
Week 4: Lesson on how to choose measurements and tools for graphical representation of data. Classroom based activity.
Week 5: Lesson on bivariate descriptive statistics with numeric variables. Classroom based activity.
Week 4 and 5: Practical session on how to do basic graphics using SPSS. Report due in at the end of the session.
Week 6: Lesson on bivariate descriptive statistics with numeric and categorical variables. Classroom based activity.
Week 7: Lesson on bivariate descriptive statistics with categorical variables. Classroom based activity.
Week 6 and 7: Practical session on contingency tables and association measurements with SPSS in a computer room. Report due in at the end of the session.