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Social Sciences Research Methods Centre course timetable

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Sat 25 Feb – Wed 8 Mar

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Monday 27 February

16:00
Meta Analysis (4 of 4) In progress 16:00 - 18:00 University Information Services, Titan Teaching Room 1, New Museums Site

Students are introduced to meta-analysis, a powerful statistical technique allowing researchers to synthesize available evidence for a given research question using standardized (comparable) effect sizes across studies. The sessions teach students how to compute treatment effects, how to compute effect sizes based on correlational studies, how to address questions such as what is the association of bullying victimization with depression? The module will be useful for students who seek to draw statistical conclusions in a standardized manner from literature reviews they are conducting.

Tuesday 28 February

14:00
Agent-based Modelling with Netlogo (2 of 2) In progress 14:00 - 18:00 8 Mill Lane, Lecture Room 6

Societies can be viewed as path-dependent dynamical systems in which the interactions between multiple heterogeneous actors, and the institutions and organisations they create, lead to complex overlapping patterns of change over different space and time-scales. Agent-based models are exploratory tools for trying to understand some of this complexity. They use computational methods to represent individual people, households, organisations, or other types of agent, and help to make explicit the potential consequences of hypotheses about the way people act, interact and engage with their environment. These types of models have been used in fields as diverse as Architecture, Archaeology, Criminology, Economics, Epidemiology, Geography, and Sociology, covering all kinds of topics including social networks and formation of social norms, spatial distribution of criminal activity, spread of disease, issues in health and welfare, warfare and disasters, behaviour in stock-markets, land-use change, farming,forestry, fisheries, traffic flow, planning and development of cities, flooding and water management. This course introduces a popular freely available software tool, Netlogo, which is accessible to those with no initial programming experience, and shows how to use it to develop a variety of simple models so that students would be able to see how it might apply to their own research.

Wednesday 1 March

09:00
Multilevel Modelling (1 of 2) Not bookable 09:00 - 13:00 8 Mill Lane, Lecture Room 5

Students are introduced to multilevel modelling techniques (a.k.a. hierarchical linear modelling). MLM allows one to analyse how contexts influence outcomes ie do schools/neighbourhoods influence behaviour.

Stata will be used during this module. No prior knowledge of Stata will be assumed.

14:00
Multilevel Modelling (2 of 2) Not bookable 14:00 - 18:00 University Information Services, Titan Teaching Room 1, New Museums Site

Students are introduced to multilevel modelling techniques (a.k.a. hierarchical linear modelling). MLM allows one to analyse how contexts influence outcomes ie do schools/neighbourhoods influence behaviour.

Stata will be used during this module. No prior knowledge of Stata will be assumed.

Thursday 2 March

14:00
Geographical Information Systems (GIS) Workshop new (4 of 4) In progress 14:00 - 17:00 Department of Geography, Downing Site - Top Lab

This is an Open Access module, so please read the course description carefully before making a booking, and be advised that spaces may be limited.

This workshop series aims to provide introductory training on Geographical Information Systems. Material covered includes the construction of geodatabases from a range of data sources, geovisualisation and mapping from geodatasets, raster-based modeling and presentation of maps and charts and other geodata outputs. Each session will start with an introductory lecture followed by practical exercises bases around tools in GIS software packages (mainly ArcGIS).

Monday 6 March

09:00
Time Series Analysis (Intensive) (1 of 2) [Full] 09:00 - 13:00 8 Mill Lane, Lecture Room 6

This module introduces the time series techniques relevant to forecasting in social science research and computer implementation of the methods. Background in basic statistical theory and regression methods is assumed. Topics covered include time series regression, moving average, exponential smoothing and decomposition. The study of applied work is emphasized in this non-specialist module.

14:00
Time Series Analysis (Intensive) (2 of 2) [Full] 14:00 - 18:00 University Information Services, Titan Teaching Room 2, New Museums Site

This module introduces the time series techniques relevant to forecasting in social science research and computer implementation of the methods. Background in basic statistical theory and regression methods is assumed. Topics covered include time series regression, moving average, exponential smoothing and decomposition. The study of applied work is emphasized in this non-specialist module.

Tuesday 7 March

09:00
Causal Inference in Quantitative Social Research (Intensive) (1 of 2) Not bookable 09:00 - 13:00 8 Mill Lane, Lecture Room 1

The challenge of causal inference is ubiquitous in social science. Nearly every research project fundamentally is about causes and effects. This course will introduce graduate students to core issues about causal inference in quantitative social research, focusing especially on how one can move from demonstrating correlation to causation. The first lecture will define key concepts of correlates, risk factors, causes, mediators and moderators. The second lecture will discuss quasi-experimental research designs (studies without random assignment), and issues of “validity” in drawing causal conclusions. The third and fourth sessions will be lectures and practicals introducing two key analytic methods (propensity score matching and fixed effects regression models) that can be used to help identify causes. The course will focus on studies in which individual people are the basic unit of analyses, particularly longitudinal studies which follow the same people over multiple waves of assessment.

14:00
Causal Inference in Quantitative Social Research (Intensive) (2 of 2) Not bookable 14:00 - 18:00 University Information Services, Titan Teaching Room 1, New Museums Site

The challenge of causal inference is ubiquitous in social science. Nearly every research project fundamentally is about causes and effects. This course will introduce graduate students to core issues about causal inference in quantitative social research, focusing especially on how one can move from demonstrating correlation to causation. The first lecture will define key concepts of correlates, risk factors, causes, mediators and moderators. The second lecture will discuss quasi-experimental research designs (studies without random assignment), and issues of “validity” in drawing causal conclusions. The third and fourth sessions will be lectures and practicals introducing two key analytic methods (propensity score matching and fixed effects regression models) that can be used to help identify causes. The course will focus on studies in which individual people are the basic unit of analyses, particularly longitudinal studies which follow the same people over multiple waves of assessment.

Wednesday 8 March

13:00
Exploratory Data Analysis and Critiques of Significance Testing new [Places] 13:00 - 17:00 8 Mill Lane, Lecture Room 4

This course will show, in a very practical way, the approach called "Exploratory Data Analysis" (EDA) where the aim is to extract useful information from data, with an enquiring, open and sceptical mind. It is, in many ways, an antidote to many advanced modelling approaches, where researchers lose touch with the richness of their data. Seeing interesting patterns in the data is the goal of EDA, rather than testing for statistical significance. The course will also consider the recent critiques of conventional "significance testing" approaches that have lead some journals to ban significance tests. Students who take this course will hopefully get more out of their data, achieve a more balanced overview of data analysis in the social sciences.

14:15
Research Ethics (Series 2) [Places] 14:15 - 17:15 Institute of Criminology, Room B3

Ethics is becoming an increasingly important issue for all researchers and the aim of these three sessions is to demonstrate the practical value of thinking seriously and systematically about what constitutes ethical conduct in social science research. The sessions will involve some small-group work.