second level university master Academic Year 2013/14 QoLexity Measuring, Monitoring and Analysis of Quality of Life and its Complexity

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1 second level university master Academic Year 2013/14 QoLexity Measuring, Monitoring and Analysis of Quality of Life and its Complexity LIST OF SUBJECTS AND TOPICS

2 A. Concepts and tools Total: 7 credits 42 hours A.1 Towards a common language: general concepts and their meanings A.1.1 Complexity 2 A.1.2 Objectivity and subjectivity 2 A.1.3 Quality and quantity 2 A.1.4 Multidimensionality 2 A.1.5 Stability and change 2 A.1.6 Explanation 2 A.1.7 Forecasting 2 A.1.8 Subjective and inter-subjective experience: different levels and dimensions 2 A.1.9 Progress and growth 2

3 A.2 Quality of life and related concepts Quality of life and its definition A.2.1 Quality of Life: review of the main concepts and domains 2 A.2.2 Measures of wellbeing: historical review 2 A.2.3 Quality of life and the capabilities approach 2 Quality of life: its declination relationship with other concepts A.2.4 The process aimed at defining the equitable and sustainable wellbeing 2 A.2.5 Quality of life and its relationship with sustainability 2 A.2.6 Quality of life and its relationship with equity, polarization, inequality 2 A.2.7 Quality of Life and urban development 2 A.2.8 Health-related quality of life 2 A.2.9 Wellbeing and identity 2 A.3 Get prepared: acquiring technical tools 1 credit (6 hours) A.3.1 Using Statistical packages: introduction to STATA 2 A.3.2 Using R: introduction 2 A.3.3 Using R: spatial statistics 2

4 B. Data Total: 12 credits 72 hours B.1 Quality-of-life data 1 6 credits (36 hours) General issues B.1.1 Social changes and official statistics changes 4 B.1.2 Monitoring and social reporting 4 B.1.3 Social statistics for social policies 4 B.1.4 GDP & beyond: the European strategy (I) 2 B.1.5 GDP & beyond: the European strategy (II) 2 Focus on particular measuring domains B.1.6 Health 2 B.1.7 Life styles 2 B.1.8 Crime 2 B.1.9 Measuring time use 2 B.1.10 Family and social networks Social participation 2 B.1.11 Education and culture 2 B.1.12 Environment and landscape 4 B.1.13 Work 4 1 This module aims at exploring (i) the role of official statistics in following social changes, and (ii) the possibility to build a narrative concerning social change through data. In particular, it will be described how observation of social phenomena through official statistics develops according to the evolution of social themes.

5 B.2 Data collection 2 6 credits (36 hours) General issues B.2.1 The new frontiers of data collection: integration of administrative data, sample surveys, census 4 B.2.2 Designing a survey: the choice of data collection technique 4 B.2.3 Designing a survey: the sample design 4 B.2.4 The art of designing a questionnaire 4 B.2.5 Designing subjective questions: international experiences 2 B.2.6 Data quality and observation errors 2 Collecting data on particular social groups and topics B.2.7 How to measure income and poverty 4 B.2.8 How to measure discrimination and stereotypes 4 B.2.9 How to measure violence against women 2 B.2.10 How to measure homelessness 2 B.2.11 Integration of sources in measuring migrants quality-of-life 4 2 This module aims at exploring the methodologies (survey design, questionnaire construction, data collection techniques) aimed at measuring social phenomena with particular reference to official statistics.

6 C. Analytical approaches Total 15 credits 90 hours C.1 Indicators: from reality to reading the reality How to make indicators a knowledge instrument C.1.1 The logical process in defining indicators 2 C.1.2 The process in selecting indicators of wellbeing 4 C.1.3 How to organize them: the system of indicators 4 C.1.4 How to relate them: composite or dashboard, synthesis and aggregation 2 Applications C.1.5 Fuzzy approach 4 C.1.6 Relational mapping 2

7 C.2 Indicators: analytical tools and strategies Aggregative approach: composite indicators C.2.1 Constructing complex indicators: technical issues. I 2 C.2.2 Constructing complex indicators: technical issues. II (counting approach, ) 2 C.2.3 Constructing complex indicators: technical issues. III (composite indicators) 4 Non aggregative approach: the case of ordinal data C.2.4 Constructing complex indicators: the partial order approach 4 C.2.5 Subjective indicators: scaling models 2 Assessing complex indicators C.2.6 Sensitivity analysis 4 C.3 Quality-of-life data analysis: pathways to modelling C.3.1 Reducing complexity of QoL data: dimensional analysis 2 C.3.2 Geographical orientation of Quality of Life data 2 C.3.3 Investigating data structure: big data and data mining 2 C.3.4 Investigating data structure: social mining 4 C.3.5 From large survey data to subpopulations: small area estimation methods (I) 4 C.3.6 From large survey data to subpopulations: small area estimation methods (II) 4

8 C.4 Quality-of-life data analysis: looking for explanations C.4.1 Relating micro and macro quality of life aspects: the multilevel approach I 4 C.4.2 Relating micro and macro quality of life aspects: the multilevel approach II 2 C.4.3 Approaches in analyzing change 2 C.4.4 Evaluating individual changes: analysis of panel quality of life data 4 C.4.5 Measuring latent, manifest and longitudinal poverty and quality of life 4 C.4.6 Life course analysis 2 C.5 Making all concrete 3 C.5.1 Relationship between quality-of-life and demographic events 2 C.5.2 Explaining life satisfaction across Europe 2 C.5.3 Territorial representation of quality-of-life data 2 C.5.4 Wellbeing and social networks 2 C.5.5 Measuring wellbeing at local level: from individuals to communities 2 C.5.6 Urban development and quality of life 2 C.5.7 Measuring vulnerability 2 C.5.8 Latent class approaches: the case of social exclusion 2 C.5.9 Using indicators to urge new policies: the Human Degeneration Index 2 3 Selected case studies as well as different and specific themes will be presented through a multidisciplinary approach and completed with lab-sections.

9 D. Representing and communicating 8 credits 48 hours D.1: Representing quality-of-life data and results D.1.1 Representing the complexity: data visualization issues 4 D.1.2 Graphics as an instrument for telling stories. Dashboards 4 D.1.3 Communication aspects of statistical graphics: how to use graphs to underline the message 2 D.1.4 How to prepare a successful presentation 4 D.1.5 How to lie with quality-of-life statistics 2 D.1.6 Shiny 2 D.2 Communicating quality-of-life results D.2.1 Public communication: the case of quality of life results 2 D.2.2 Strategies in communicating information on QoL Data, media and public opinion: problems and strategies D.2.3 Statistics and political communication: theories and methods 4 D.2.4 How knowledge can be transferred into policy 2 D.2.5 Communication and policy use of indicators 2 D.2.6 Politics, policy and quality of democracy 2 6

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