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Social Sciences Research Methods Programme course timetable

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Tue 17 Nov 2020 – Wed 2 Dec 2020

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Tuesday 17 November 2020

10:00
Doing Qualitative Interviews (2 of 3) Finished 10:00 - 10:30 SSRMP Zoom

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

14:00
Introduction to Stata (2 of 2) Finished 14:00 - 18:00 Taught Online

The course will provide students with an introduction to the popular and powerful statistics package Stata. Stata is commonly used by analysts in both the social and natural sciences, and is the statistics package used most widely by the SSRMP. You will learn:

  • How to open and manage a dataset in Stata
  • How to recode variables
  • How to select a sample for analysis
  • The commands needed to perform simple statistical analyses in Stata
  • Where to find additional resources to help you as you progress with Stata

The first day (4 hours) is a mix between pre-recorded videos and exercises that students can do by themselves. There is no live session except a 45 minutes technical assistance for those who have problems with Stata or the computer.

The second day (4 hours) contains one-hour live lecture and a .zoom exercise. The audio for the one-hour live lecture will be recoded and the answers to the final exercise will be available on the Moodle.

The course is intended for students who already have a working knowledge of statistics - it's designed primarily as a ""second language"" course for students who are already familiar with another package, perhaps R or SPSS. Students who don't already have a working knowledge of applied statistics should look at courses in our Basic Statistics Stream.

Wednesday 18 November 2020

10:00
Basic Quantitative Analysis (BQA-3) (3 of 4) Finished 10:00 - 12:00 SSRMP pre-recorded lecture online

Building upon the univariate techniques introduced in the Foundations in Applied Statistics (FiAS) module, these sessions aim to provide students with a thorough understanding of statistical methods designed to test associations between two variables (bivariate statistics). Students will learn about the assumptions underlying each test, and will receive practical instruction on how to generate and interpret bivariate results using Stata. It introduces students to four of the most commonly used statistical tests in the social sciences: correlation, chi-square tests, t-tests, and analysis of variance (ANOVA).

The module is divided between pre-recorded mini-lectures, in which you'll learn the relevant theory, and hands-on live practical sessions in Zoom, in which you will learn how to apply these techniques to analyse real data using the statistical package, Stata.

You will learn the following techniques:

  • Cross-tabulations
  • Scatterplots
  • Covariance and correlation
  • Nonparametric methods
  • Two-sample t-tests
  • ANOVA

As well as viewing the pre-recorded mini lectures via Moodle and attending the live lab sessions, students are expected to do a few hours of independent study each week.

Basic Quantitative Analysis (BQA-4) (3 of 4) Finished 10:00 - 12:00 SSRMP pre-recorded lecture online

Building upon the univariate techniques introduced in the Foundations in Applied Statistics (FiAS) module, these sessions aim to provide students with a thorough understanding of statistical methods designed to test associations between two variables (bivariate statistics). Students will learn about the assumptions underlying each test, and will receive practical instruction on how to generate and interpret bivariate results using Stata. It introduces students to four of the most commonly used statistical tests in the social sciences: correlation, chi-square tests, t-tests, and analysis of variance (ANOVA).

The module is divided between pre-recorded mini-lectures, in which you'll learn the relevant theory, and hands-on live practical sessions in Zoom, in which you will learn how to apply these techniques to analyse real data using the statistical package, Stata.

You will learn the following techniques:

  • Cross-tabulations
  • Scatterplots
  • Covariance and correlation
  • Nonparametric methods
  • Two-sample t-tests
  • ANOVA

As well as viewing the pre-recorded mini lectures via Moodle and attending the live lab sessions, students are expected to do a few hours of independent study each week.

14:00
Basic Quantitative Analysis (BQA-3) (4 of 4) Finished 14:00 - 16:00 SSRMP Zoom

Building upon the univariate techniques introduced in the Foundations in Applied Statistics (FiAS) module, these sessions aim to provide students with a thorough understanding of statistical methods designed to test associations between two variables (bivariate statistics). Students will learn about the assumptions underlying each test, and will receive practical instruction on how to generate and interpret bivariate results using Stata. It introduces students to four of the most commonly used statistical tests in the social sciences: correlation, chi-square tests, t-tests, and analysis of variance (ANOVA).

The module is divided between pre-recorded mini-lectures, in which you'll learn the relevant theory, and hands-on live practical sessions in Zoom, in which you will learn how to apply these techniques to analyse real data using the statistical package, Stata.

You will learn the following techniques:

  • Cross-tabulations
  • Scatterplots
  • Covariance and correlation
  • Nonparametric methods
  • Two-sample t-tests
  • ANOVA

As well as viewing the pre-recorded mini lectures via Moodle and attending the live lab sessions, students are expected to do a few hours of independent study each week.

16:00
Basic Quantitative Analysis (BQA-4) (4 of 4) Finished 16:00 - 18:00 SSRMP Zoom

Building upon the univariate techniques introduced in the Foundations in Applied Statistics (FiAS) module, these sessions aim to provide students with a thorough understanding of statistical methods designed to test associations between two variables (bivariate statistics). Students will learn about the assumptions underlying each test, and will receive practical instruction on how to generate and interpret bivariate results using Stata. It introduces students to four of the most commonly used statistical tests in the social sciences: correlation, chi-square tests, t-tests, and analysis of variance (ANOVA).

The module is divided between pre-recorded mini-lectures, in which you'll learn the relevant theory, and hands-on live practical sessions in Zoom, in which you will learn how to apply these techniques to analyse real data using the statistical package, Stata.

You will learn the following techniques:

  • Cross-tabulations
  • Scatterplots
  • Covariance and correlation
  • Nonparametric methods
  • Two-sample t-tests
  • ANOVA

As well as viewing the pre-recorded mini lectures via Moodle and attending the live lab sessions, students are expected to do a few hours of independent study each week.

Thursday 19 November 2020

12:00
Geographical Information Systems (GIS) Workshop (3 of 4) Finished 12:00 - 13:00 SSRMP Zoom

This module is shared with Geography. Students from the Department of Geography MUST book places on this course via the Department; any bookings made by Geography students via the SSRMC portal will be cancelled.

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 using GIS software.

Monday 23 November 2020

09:00
Introduction to Python (1 of 2) Finished 09:00 - 14:00 SSRMP Zoom

This module introduces the use of Python, a free programming language originally developed for statistical data analysis. Students will learn:

  • Ways of reading data into Python
  • How to manipulate data in major data types
  • How to draw basic graphs and figures with Python
  • 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.

10:00
Doing Multivariate Analysis (DMA-1) (1 of 4) Finished 10:00 - 12:00 SSRMP Zoom

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.

14:00
Doing Multivariate Analysis (DMA-1) (2 of 4) Finished 14:00 - 16:00 SSRMP Zoom

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.

15:00
Researching Organisations (3 of 3) Finished 15:00 - 17:00 Taught Online

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 the problems that are typically encountered in undertaking such studies.

16:00
Introduction to Python (2 of 2) Finished 16:00 - 17:00 SSRMP Zoom

This module introduces the use of Python, a free programming language originally developed for statistical data analysis. Students will learn:

  • Ways of reading data into Python
  • How to manipulate data in major data types
  • How to draw basic graphs and figures with Python
  • 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.

Tuesday 24 November 2020

10:00
Doing Qualitative Interviews (3 of 3) Finished 10:00 - 10:30 SSRMP Zoom

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

Wednesday 25 November 2020

10:00
Doing Multivariate Analysis (DMA-3) (1 of 4) Finished 10:00 - 12:00 SSRMP Zoom

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.

Doing Multivariate Analysis (DMA-2) (1 of 4) Finished 10:00 - 12:00 SSRMP Zoom

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.

14:00
Doing Multivariate Analysis (DMA-2) (2 of 4) Finished 14:00 - 16:00 SSRMP Zoom

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.

16:00
Doing Multivariate Analysis (DMA-3) (2 of 4) Finished 16:00 - 18:00 SSRMP Zoom

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.

Thursday 26 November 2020

12:00
Geographical Information Systems (GIS) Workshop (4 of 4) Finished 12:00 - 13:00 SSRMP Zoom

This module is shared with Geography. Students from the Department of Geography MUST book places on this course via the Department; any bookings made by Geography students via the SSRMC portal will be cancelled.

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 using GIS software.

Monday 30 November 2020

10:00
Doing Multivariate Analysis (DMA-1) (3 of 4) Finished 10:00 - 12:00 SSRMP Zoom

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.

14:00
Doing Multivariate Analysis (DMA-1) (4 of 4) Finished 14:00 - 16:00 SSRMP Zoom

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.

16:00
Merging and Linking Data Sets Finished 16:00 - 18:00 SSRMP Zoom

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.

Wednesday 2 December 2020

10:00
Doing Multivariate Analysis (DMA-3) (3 of 4) Finished 10:00 - 12:00 SSRMP Zoom

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.

Doing Multivariate Analysis (DMA-2) (3 of 4) Finished 10:00 - 12:00 SSRMP Zoom

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.

14:00
Doing Multivariate Analysis (DMA-2) (4 of 4) Finished 14:00 - 16:00 SSRMP Zoom

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.

16:00
Doing Multivariate Analysis (DMA-3) (4 of 4) Finished 16:00 - 18:00 SSRMP Zoom

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.