Social Sciences Research Methods Programme course timetable
Tuesday 6 March 2018
14:00 |
Secondary Data Analysis
Finished
Using secondary data (that is, data collected by someone else, usually a government agency or large research organisation) has a number of advantages in social science research: sample sizes are usually larger than can be achieved by primary data collection, samples are more nearly representative of the populations they are drawn from, and using secondary data for a research project often represents significant savings in time and money. This short course, taught by Dr Deborah Wiltshire of the UK Data Archive, will discuss the advantages and limitations of using secondary data for research in the social sciences, and will introduce students to the wide range of available secondary data sources. The course is based in a computer lab; students will learn how to search online for suitable secondary data by browsing the database of the UK Data Archive. |
Wednesday 7 March 2018
13:00 |
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. Topics:
Note: this module was originally advertised as also covering fixed-effects regression models. Fixed-effects models have now been dropped from the content; students wishing to learn about them should attend the SSRMC module on panel data methods https://www.training.cam.ac.uk/jsss/event/2141519 |
14:00 |
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. Topics:
Note: this module was originally advertised as also covering fixed-effects regression models. Fixed-effects models have now been dropped from the content; students wishing to learn about them should attend the SSRMC module on panel data methods https://www.training.cam.ac.uk/jsss/event/2141519 |
Wednesday 14 March 2018
09:00 |
Panel Data Analysis (Intensive)
Finished
This module provides an applied introduction to panel data analysis (PDA). Panel data are gathered by taking repeated observations from a series of research units (eg. individuals, firms) as they move through time. This course focuses primarily on panel data with a large number of research units tracked for a relatively small number of time points. The module begins by introducing key concepts, benefits and pitfalls of PDA. Students are then taught how to manipulate and describe panel data in Stata. The latter part of the module introduces random and fixed effects panel models for continuous and dichotomous outcomes. The course is taught through a mixture of lectures and practical sessions designed to give students hands-on experience of working with real-world data from the British Household Panel Survey.
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14:00 |
Panel Data Analysis (Intensive)
Finished
This module provides an applied introduction to panel data analysis (PDA). Panel data are gathered by taking repeated observations from a series of research units (eg. individuals, firms) as they move through time. This course focuses primarily on panel data with a large number of research units tracked for a relatively small number of time points. The module begins by introducing key concepts, benefits and pitfalls of PDA. Students are then taught how to manipulate and describe panel data in Stata. The latter part of the module introduces random and fixed effects panel models for continuous and dichotomous outcomes. The course is taught through a mixture of lectures and practical sessions designed to give students hands-on experience of working with real-world data from the British Household Panel Survey.
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Monday 19 March 2018
10:00 |
Evaluation Methods
Finished
This course aims to provide students with a range of specific technical skills that will enable them to undertake impact evaluation of policy. Too often policy is implemented but not fully evaluated. Without evaluation we cannot then tell what the short or longer term impact of a particular policy has been. On this course, students will learn the skills needed to evaluate particular policies and will have the opportunity to do some hands on data manipulation. A particular feature of this course is that it provides these skills in a real world context of policy evaluation. It also focuses primarily not on experimental evaluation (Random Control Trials) but rather quasi-experimental methodologies that can be used where an experiment is not desirable or feasible. Topics:
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13:45 |
Evaluation Methods
Finished
This course aims to provide students with a range of specific technical skills that will enable them to undertake impact evaluation of policy. Too often policy is implemented but not fully evaluated. Without evaluation we cannot then tell what the short or longer term impact of a particular policy has been. On this course, students will learn the skills needed to evaluate particular policies and will have the opportunity to do some hands on data manipulation. A particular feature of this course is that it provides these skills in a real world context of policy evaluation. It also focuses primarily not on experimental evaluation (Random Control Trials) but rather quasi-experimental methodologies that can be used where an experiment is not desirable or feasible. Topics:
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Tuesday 20 March 2018
10:00 |
Evaluation Methods
Finished
This course aims to provide students with a range of specific technical skills that will enable them to undertake impact evaluation of policy. Too often policy is implemented but not fully evaluated. Without evaluation we cannot then tell what the short or longer term impact of a particular policy has been. On this course, students will learn the skills needed to evaluate particular policies and will have the opportunity to do some hands on data manipulation. A particular feature of this course is that it provides these skills in a real world context of policy evaluation. It also focuses primarily not on experimental evaluation (Random Control Trials) but rather quasi-experimental methodologies that can be used where an experiment is not desirable or feasible. Topics:
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13:30 |
Evaluation Methods
Finished
This course aims to provide students with a range of specific technical skills that will enable them to undertake impact evaluation of policy. Too often policy is implemented but not fully evaluated. Without evaluation we cannot then tell what the short or longer term impact of a particular policy has been. On this course, students will learn the skills needed to evaluate particular policies and will have the opportunity to do some hands on data manipulation. A particular feature of this course is that it provides these skills in a real world context of policy evaluation. It also focuses primarily not on experimental evaluation (Random Control Trials) but rather quasi-experimental methodologies that can be used where an experiment is not desirable or feasible. Topics:
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Wednesday 25 April 2018
09:30 |
Standard statistical techniques in the social sciences are good at uncovering relationships between variables, but less good at establishing whether these relationships are causal. If A and B are correlated, does that mean A "causes" B? That B "causes" A? Or could both A and B be driven by a third factor C? Randomised controlled trials are a type of study often considered to be the gold standard in uncovering this kind of causality. Many students and early-career researchers avoid RCTs, assuming they are complex and expensive to run. However, that need not be the case. This module will explain the theory of RCTs, how they are implemented, and will encourage participants to think about how they might design an RCT in their own field of work. |
14:00 |
Standard statistical techniques in the social sciences are good at uncovering relationships between variables, but less good at establishing whether these relationships are causal. If A and B are correlated, does that mean A "causes" B? That B "causes" A? Or could both A and B be driven by a third factor C? Randomised controlled trials are a type of study often considered to be the gold standard in uncovering this kind of causality. Many students and early-career researchers avoid RCTs, assuming they are complex and expensive to run. However, that need not be the case. This module will explain the theory of RCTs, how they are implemented, and will encourage participants to think about how they might design an RCT in their own field of work. |
Monday 30 April 2018
14:00 |
This course will introduce students to 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 led 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.
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Wednesday 9 May 2018
14:00 |
Research Ethics (Lent) - Rescheduled
Finished
Please note - due to the change of lecturer, the description and some of the materials/reading for this module may change. Ethics is becoming an increasingly important issue for all researchers and the aim of this session is to demonstrate the practical value of thinking seriously and systematically about what constitutes ethical conduct in social science research. The session will involve some small-group work. |
Wednesday 3 October 2018
16:00 |
SSRMC Student Induction Lecture
Finished
This event details how the SSRMC works, more about the modules we offer, and everything you need to know about making a booking. NB. ALL STUDENTS WISHING TO TAKE SSRMC COURSES THIS YEAR ARE EXPECTED TO ATTEND THIS INDUCTION SESSION |
Thursday 4 October 2018
10:00 |
This module is shared with Psychology. Students from the Department of Psychology MUST book places on this course via the Department; any bookings made by Psychology students via the SSRMC portal will be cancelled. The course focuses on practical hands-on variable handling and programming implementation using rather than on theory. This course is intended for those who have never programmed before, including those who only call/run Matlab scripts but are not familiar with how code works and how matrices are handled in Matlab. (Note that calling a couple of scripts is not 'real' programming.) MATLAB (C) is a powerful scientific programming environment optimal for data analysis and engineering solutions. More information on the programme and its uses can be found here: https://www.mathworks.com/products/matlab.html More information on the course can be found, here: http://www.psychol.cam.ac.uk/grads/grads/pg-prog/programming#section-0 |
14:00 |
This module is shared with Psychology. Students from the Department of Psychology MUST book places on this course via the Department; any bookings made by Psychology students via the SSRMC portal will be cancelled. The course focuses on practical hands-on variable handling and programming implementation using rather than on theory. This course is intended for those who have never programmed before, including those who only call/run Matlab scripts but are not familiar with how code works and how matrices are handled in Matlab. (Note that calling a couple of scripts is not 'real' programming.) MATLAB (C) is a powerful scientific programming environment optimal for data analysis and engineering solutions. More information on the programme and its uses can be found here: https://www.mathworks.com/products/matlab.html More information on the course can be found, here: http://www.psychol.cam.ac.uk/grads/grads/pg-prog/programming#section-0 |
Friday 5 October 2018
10:00 |
This module is shared with Psychology. Students from the Department of Psychology MUST book places on this course via the Department; any bookings made by Psychology students via the SSRMC portal will be cancelled. The course focuses on practical hands-on variable handling and programming implementation using rather than on theory. This course is intended for those who have never programmed before, including those who only call/run Matlab scripts but are not familiar with how code works and how matrices are handled in Matlab. (Note that calling a couple of scripts is not 'real' programming.) MATLAB (C) is a powerful scientific programming environment optimal for data analysis and engineering solutions. More information on the programme and its uses can be found here: https://www.mathworks.com/products/matlab.html More information on the course can be found, here: http://www.psychol.cam.ac.uk/grads/grads/pg-prog/programming#section-0 |
15:30 |
This module is shared with Psychology. Students from the Department of Psychology MUST book places on this course via the Department; any bookings made by Psychology students via the SSRMC portal will be cancelled. The course focuses on practical hands-on variable handling and programming implementation using rather than on theory. This course is intended for those who have never programmed before, including those who only call/run Matlab scripts but are not familiar with how code works and how matrices are handled in Matlab. (Note that calling a couple of scripts is not 'real' programming.) MATLAB (C) is a powerful scientific programming environment optimal for data analysis and engineering solutions. More information on the programme and its uses can be found here: https://www.mathworks.com/products/matlab.html More information on the course can be found, here: http://www.psychol.cam.ac.uk/grads/grads/pg-prog/programming#section-0 |
Monday 8 October 2018
14:00 |
Introduction to Empirical Research
Finished
This module is for anyone considering studying on an SSRMC module but not sure which one/s to choose. It provides an overview of the research process and issues in research design. Through reflection on a broad overview of empirical research, the module aims to encourage students to consider where they may wish to develop their research skills and knowledge. The module will signpost the different modules, both quantitative and qualitative, offered by SSRMC and encourage students to consider what modules might be appropriate for their research and career development. You will learn:
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17:00 |
Introduction to Empirical Research
Finished
This module is for anyone considering studying on an SSRMC module but not sure which one/s to choose. It provides an overview of the research process and issues in research design. Through reflection on a broad overview of empirical research, the module aims to encourage students to consider where they may wish to develop their research skills and knowledge. The module will signpost the different modules, both quantitative and qualitative, offered by SSRMC and encourage students to consider what modules might be appropriate for their research and career development. You will learn:
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Tuesday 9 October 2018
14:00 |
Psychometrics
Finished
An introduction to the design, validation and implementation of tests and questionnaires in social science research, using both Classical Test Theory (CTT) and modern psychometric methods such as Item Response Theory (IRT). This course aims to enable students to: be able to construct and validate a test or questionnaire; understand the strengths, weaknesses and limitations of existing tests and questionnaires; appreciate the impact and potential of modern psychometric methods in the internet age. Week 1: Introduction to psychometrics Week 2: Testing in the online environment Week 3: Modern Psychometrics Week 4: Implementing adaptive tests online |
16:00 |
Comparative Historical Methods
Finished
These four sessions will introduce students to comparative historical research methods, emphasizing their qualitative dimensions. In the first session, we will analyze some contemporary classics within this genre. In the second and third sessions, we will review and distinguish among a variety of intellectual justifications for this genre as a methodology. In the final session, we will focus on a "state of the art" defence of qualitative and comparative-historical research, both in theory and practice. |
Wednesday 10 October 2018
16:00 |
This course will introduce students to the general philosophical debates concerning scientific methodology, assessing their ramifications for the conduct of qualitative social research. It will enable students to critically evaluate major programmes in the philosophy of sciences, considering whether there are important analytic differences between the social and natural sciences; and whether qualitative methods themselves comprise a unified approach to the study of social reality. |
Monday 15 October 2018
13:00 |
Ethics in Data Collection and Use
Finished
This is an introductory course for students whose research involves collecting, storing or analysing data using networked digital devices. Unless your research data is only collected using pen and paper or tape recorders and is written up on a manual typewriter, this course will be relevant to you. If you are planning to collect data online through either public or private communications, or you intend to share or publish data collected by other means it will be essential. |
15:00 |
Research Ethics (Michaelmas)
Finished
Ethics is becoming an increasingly important issue for all researchers and the aim of this session is to demonstrate the practical value of thinking seriously and systematically about what constitutes ethical conduct in social science research. The session will involve a lecture component and some small-group work. Aims: Topics:
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