Social Sciences Research Methods Programme course timetable

This module will introduce you to the theory and practice of multivariate analysis, covering Ordinary Least Squares (OLS) and logistic regressions. You will learn how to read published results critically, to do simple multivariate modelling yourself, and to interpret and write about your results intelligently.

Half of the module is based in the lecture theatre, and covers the theory behind multivariate regression; the other half is lab-based, in which students will work through practical exercises using statistical software.

To get the most out of the course, you should also expect to spend some time between sessions having fun by building your own statistical models.

NOTE: Strike action is taking place between 25 November and 4 December 2019. If the strike goes ahead, this module will be affected. Please see the 'latest news' section on the home page of the SSRMP website for more information.

This course provides an introduction to some of the methodological issues involved in researching organisations. Drawing on examples of studies carried out in a wide range of different types of organisation, the aim will be to explore practical strategies to overcome some of problems that are typically encountered in undertaking such studies.

NOTE: Strike action is taking place between 25 November and 4 December 2019. If the strike goes ahead, this module may be affected. Please see the 'latest news' section on the home page of the SSRMP website for more information.

Face-to-face interviews are used to collect a wide range of information in the social sciences. They are appropriate for the gathering of information on individual and institutional patterns of behaviour; complex histories or processes; identities and cultural meanings; routines that are not written down; and life-history events. Face-to-face interviews thus comprise an appropriate method to generate information on individual behaviour, the reasons for certain patterns of acting and talking, and the type of connection people have with each other.

The first session provides an overview of interviewing as a social research method, then focuses on the processes of organising and conducting qualitative interviews. The second session explores the ethics and practical constraints of interviews as a research method, particularly relevant when attempting to engage with marginalised or stigmatised communities. The third session focuses on organisation and analysis after interviews, including interpretation through coding and close reading. This session involves practical examples from qualitative analysis software. The final session provides an opportunity for a hands-on session, to which students should bring their interview material (at whatever stage of the process: whether writing interview questions, coding or analysing data) in order to receive advice and support in taking the interview material/data to the next stage of the research process.

Topics:

1. Conducting qualitative interviews

2. Ethics and practical constraints

3. Practical session: interpretation and analysis

NOTE: Strike action is taking place between 25 November and 4 December 2019. If the strike goes ahead, this module will be affected. Please see the 'latest news' section on the home page of the SSRMP website for more information.

These two sessions will provide a basic introduction to the management and analysis of relational databases, using Microsoft Access and a set of historical datasets. The workshops will introduce participants to the following:

• The use of Access’s menus and tool bars
• Viewing and browsing data tables
• Creating quick forms formulating queries
• Developing queries using Boolean operators
• Performing simple statistical operations
• Linking tables and working with linked tables
• Querying multiple tables
• Data transformation.

NOTE: Strike action is taking place between 25 November and 4 December 2019. If the strike goes ahead, this module will be affected. Please see the 'latest news' section on the home page of the SSRMP website for more information.

This course provides an introduction to some of the methodological issues involved in researching organisations. Drawing on examples of studies carried out in a wide range of different types of organisation, the aim will be to explore practical strategies to overcome some of problems that are typically encountered in undertaking such studies.

NOTE: Strike action is taking place between 25 November and 4 December 2019. If the strike goes ahead, this module may be affected. Please see the 'latest news' section on the home page of the SSRMP website for more information.

This module will introduce you to the theory and practice of multivariate analysis, covering Ordinary Least Squares (OLS) and logistic regressions. You will learn how to read published results critically, to do simple multivariate modelling yourself, and to interpret and write about your results intelligently.

Half of the module is based in the lecture theatre, and covers the theory behind multivariate regression; the other half is lab-based, in which students will work through practical exercises using statistical software.

To get the most out of the course, you should also expect to spend some time between sessions having fun by building your own statistical models.

NOTE: Strike action is taking place between 25 November and 4 December 2019. If the strike goes ahead, this module will be affected. Please see the 'latest news' section on the home page of the SSRMP website for more information.

This module will introduce you to the theory and practice of multivariate analysis, covering Ordinary Least Squares (OLS) and logistic regressions. You will learn how to read published results critically, to do simple multivariate modelling yourself, and to interpret and write about your results intelligently.

Half of the module is based in the lecture theatre, and covers the theory behind multivariate regression; the other half is lab-based, in which students will work through practical exercises using statistical software.

To get the most out of the course, you should also expect to spend some time between sessions having fun by building your own statistical models.

NOTE: Strike action is taking place between 25 November and 4 December 2019. If the strike goes ahead, this module will be affected. Please see the 'latest news' section on the home page of the SSRMP website for more information.

This module will introduce you to the theory and practice of multivariate analysis, covering Ordinary Least Squares (OLS) and logistic regressions. You will learn how to read published results critically, to do simple multivariate modelling yourself, and to interpret and write about your results intelligently.

Half of the module is based in the lecture theatre, and covers the theory behind multivariate regression; the other half is lab-based, in which students will work through practical exercises using statistical software.

To get the most out of the course, you should also expect to spend some time between sessions having fun by building your own statistical models.

NOTE: Strike action is taking place between 25 November and 4 December 2019. If the strike goes ahead, this module will be affected. Please see the 'latest news' section on the home page of the SSRMP website for more information.

This module will introduce you to the theory and practice of multivariate analysis, covering Ordinary Least Squares (OLS) and logistic regressions. You will learn how to read published results critically, to do simple multivariate modelling yourself, and to interpret and write about your results intelligently.

Half of the module is based in the lecture theatre, and covers the theory behind multivariate regression; the other half is lab-based, in which students will work through practical exercises using statistical software.

To get the most out of the course, you should also expect to spend some time between sessions having fun by building your own statistical models.

NOTE: Strike action is taking place between 25 November and 4 December 2019. If the strike goes ahead, this module will be affected. Please see the 'latest news' section on the home page of the SSRMP website for more information.

This module will introduce you to the theory and practice of multivariate analysis, covering Ordinary Least Squares (OLS) and logistic regressions. You will learn how to read published results critically, to do simple multivariate modelling yourself, and to interpret and write about your results intelligently.

Half of the module is based in the lecture theatre, and covers the theory behind multivariate regression; the other half is lab-based, in which students will work through practical exercises using statistical software.

To get the most out of the course, you should also expect to spend some time between sessions having fun by building your own statistical models.

NOTE: Strike action is taking place between 25 November and 4 December 2019. If the strike goes ahead, this module will be affected. Please see the 'latest news' section on the home page of the SSRMP website for more information.

Merging and linking data sets are a process that researchers often encounter. In most cohort studies and longitudinal data sets, data on the same respondents who were interviewed at various times may be stored in different files. Or, data on different respondents but were interviewed at the same time, such as mothers and their children, may also be stored in various files. In either case, we may want to merge/link the files together before performing further analyses. This course will discuss two different ways of combining data files: merge (one-to-one merging and one-to-many merging) and append, and will demonstrate how to use ‘merge’ and ‘append’ commands in Stata.

These two sessions will provide a basic introduction to the management and analysis of relational databases, using Microsoft Access and a set of historical datasets. The workshops will introduce participants to the following:

• The use of Access’s menus and tool bars
• Viewing and browsing data tables
• Creating quick forms formulating queries
• Developing queries using Boolean operators
• Performing simple statistical operations
• Linking tables and working with linked tables
• Querying multiple tables
• Data transformation.

NOTE: Strike action is taking place between 25 November and 4 December 2019. If the strike goes ahead, this module will be affected. Please see the 'latest news' section on the home page of the SSRMP website for more information.

This module will introduce you to the theory and practice of multivariate analysis, covering Ordinary Least Squares (OLS) and logistic regressions. You will learn how to read published results critically, to do simple multivariate modelling yourself, and to interpret and write about your results intelligently.

Half of the module is based in the lecture theatre, and covers the theory behind multivariate regression; the other half is lab-based, in which students will work through practical exercises using statistical software.

To get the most out of the course, you should also expect to spend some time between sessions having fun by building your own statistical models.

NOTE: Strike action is taking place between 25 November and 4 December 2019. If the strike goes ahead, this module will be affected. Please see the 'latest news' section on the home page of the SSRMP website for more information.

This module will introduce you to the theory and practice of multivariate analysis, covering Ordinary Least Squares (OLS) and logistic regressions. You will learn how to read published results critically, to do simple multivariate modelling yourself, and to interpret and write about your results intelligently.

Half of the module is based in the lecture theatre, and covers the theory behind multivariate regression; the other half is lab-based, in which students will work through practical exercises using statistical software.

To get the most out of the course, you should also expect to spend some time between sessions having fun by building your own statistical models.

NOTE: Strike action is taking place between 25 November and 4 December 2019. If the strike goes ahead, this module will be affected. Please see the 'latest news' section on the home page of the SSRMP website for more information.

This module will introduce you to the theory and practice of multivariate analysis, covering Ordinary Least Squares (OLS) and logistic regressions. You will learn how to read published results critically, to do simple multivariate modelling yourself, and to interpret and write about your results intelligently.

Half of the module is based in the lecture theatre, and covers the theory behind multivariate regression; the other half is lab-based, in which students will work through practical exercises using statistical software.

To get the most out of the course, you should also expect to spend some time between sessions having fun by building your own statistical models.

NOTE: Strike action is taking place between 25 November and 4 December 2019. If the strike goes ahead, this module will be affected. Please see the 'latest news' section on the home page of the SSRMP website for more information.

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.

This module introduces the use of R, a free programming language originally developed for statistical data analysis. In this course, we will use R through R Studio, a user-friendly interface. Students will learn:

• Ways of reading data into R
• How to manipulate data in major data types
• How to draw basic graphs and figures with R
• How to summarise data using descriptive statistics
• How to perform basic inferential statistics

This module is suitable for students who have no prior experience in programming, but participants will be assumed to have a good working knowledge of basic statistical techniques.

For an online example of how R can be used: https://www.ssc.wisc.edu/sscc/pubs/RFR/RFR_Introduction.html'''

The module will introduce students to the study of language use as a distinctive type of social practice. Attention will be focused primarily on the methodological and analytic principles of conversation analysis. (CA). However, it will explore the debates between CA and Critical Discourse Analysis (CDA), as a means of addressing the relationship between the study of language use and the study of other aspects of social life. It will also consider the roots of conversation analysis in the research initiatives of ethnomethodology, and the analysis of ordinary and institutional talk. It will finally consider the interface between CA and CDA.

Topics:

• Session 1: The Roots of Conversation Analysis
• Session 2: Ordinary Talk
• Session 3: Institutional Talk
• Session 4: Conversation Analysis and Critical Discourse Analysis

This module introduces the use of R, a free programming language originally developed for statistical data analysis. In this course, we will use R through R Studio, a user-friendly interface. Students will learn:

• Ways of reading data into R
• How to manipulate data in major data types
• How to draw basic graphs and figures with R
• How to summarise data using descriptive statistics
• How to perform basic inferential statistics

This module is suitable for students who have no prior experience in programming, but participants will be assumed to have a good working knowledge of basic statistical techniques.

For an online example of how R can be used: https://www.ssc.wisc.edu/sscc/pubs/RFR/RFR_Introduction.html'''

This is an introductory course for students who have little or no prior training in statistics. The module is divided between lectures, in which you'll learn the relevant theory, and hands-on practical sessions, in which you will learn how to analyze real data using the statistical package Stata. You will learn:

• The key features of quantitative analysis, and how it differs from other types of empirical analysis
• Basic concepts: what is a variable? what is the distribution of a variable? and how can we best represent a distribution graphically?
• Features of statistical distributions: measures of central tendency and dispersion
• The normal distribution
• The basics of formal hypothesis testing
• Why statistical testing works
• Statistical methods used to test simple hypotheses
• How to use Stata

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.

This is an introductory course for students who have little or no prior training in statistics. The module is divided between lectures, in which you'll learn the relevant theory, and hands-on practical sessions, in which you will learn how to analyze real data using the statistical package Stata. You will learn:

• The key features of quantitative analysis, and how it differs from other types of empirical analysis
• Basic concepts: what is a variable? what is the distribution of a variable? and how can we best represent a distribution graphically?
• Features of statistical distributions: measures of central tendency and dispersion
• The normal distribution
• The basics of formal hypothesis testing
• Why statistical testing works
• Statistical methods used to test simple hypotheses
• How to use Stata