Social Sciences Research Methods Programme course timetable

*DO NOT book for this course if you are already booked for Foundations in Applied Statistics (which includes an introduction to R) as your booking will be cancelled

This module is part of the Social Science Research Methods Centre training programme which is a shared platform for providing research students with a broad range of quantitative and qualitative research methods skills that are relevant across the social sciences.

This workshop introduces students to one of the most frequently used statistics packages for social sciences, R. Students will learn how to download and install R, enter simple data into R, how to load data sets from other statistical packages into R, how to use the R environment for simple calculations, elementary graphs and tables. The module will introduce the use of code for performing these operations. This module is intended primarily for students who have not previously used R and who also do not have much previous experience with statistics. This is not a statistical methods course.

The SSRMC Administrator will make all bookings for this module. If you would like to follow the module you must complete the SSRMC skills audit by 4pm on Thursday 8 October before a place can be booked for you.

If you have already completed the audit you may have had a place booked for you by your Department. Please check this by typing your CRSid into the search box at the very top right of this page, hitting the enter key then clicking on your name. This will show the module(s) you are booked for, as applicable.

This module is part of the Social Science Research Methods Centre training programme which is a shared platform for providing research students with a broad range of quantitative and qualitative research methods skills that are relevant across the social sciences.

This foundational course is for graduate students who have no prior training in statistics.

Topics covered include: the notion of variables and how they are measured; ways of describing the central tendency and the dispersion of a variable; and the principles of hypothesis testing and statistical significance. The course also introduces students to the software R. Each session consists of a lecture part, and a computer lab part with exercises in R.

The SSRMC Administrator will make all bookings for this module. If you would like to follow the module you must complete the SSRMC skills audit by 4pm on Thursday 8 October before a place can be booked for you.

If you have already completed the audit you may have had a place booked for you by your Department. Please check this by typing your CRSid into the search box at the very top right of this page, hitting the enter key then clicking on your name. This will show the module(s) you are booked for, as applicable.

This module is part of the Social Science Research Methods Centre training programme which is a shared platform for providing research students with a broad range of quantitative and qualitative research methods skills that are relevant across the social sciences.

This foundational course is for graduate students who have no prior training in statistics.

Topics covered include: the notion of variables and how they are measured; ways of describing the central tendency and the dispersion of a variable; and the principles of hypothesis testing and statistical significance. The course also introduces students to the software R. Each session consists of a lecture part, and a computer lab part with exercises in R.

The SSRMC Administrator will make all bookings for this module. If you would like to follow the module you must complete the SSRMC skills audit by 4pm on Thursday 8 October before a place can be booked for you.

If you have already completed the audit you may have had a place booked for you by your Department. Please check this by typing your CRSid into the search box at the very top right of this page, hitting the enter key then clicking on your name. This will show the module(s) you are booked for, as applicable.

This module is part of the Social Science Research Methods Centre training programme which is a shared platform for providing research students with a broad range of quantitative and qualitative research methods skills that are relevant across the social sciences.

This foundational course is for graduate students who have no prior training in statistics.

Topics covered include: the notion of variables and how they are measured; ways of describing the central tendency and the dispersion of a variable; and the principles of hypothesis testing and statistical significance. The course also introduces students to the software R. Each session consists of a lecture part, and a computer lab part with exercises in R.

*DO NOT book for this course if you are already booked for Foundations in Applied Statistics (which includes an introduction to R) as your booking will be cancelled

This module is part of the Social Science Research Methods Centre training programme which is a shared platform for providing research students with a broad range of quantitative and qualitative research methods skills that are relevant across the social sciences.

This workshop introduces students to one of the most frequently used statistics packages for social sciences, R. Students will learn how to download and install R, enter simple data into R, how to load data sets from other statistical packages into R, how to use the R environment for simple calculations, elementary graphs and tables. The module will introduce the use of code for performing these operations. This module is intended primarily for students who have not previously used R and who also do not have much previous experience with statistics. This is not a statistical methods course.

*DO NOT book for this course if you are already booked for Foundations in Applied Statistics (which includes an introduction to R) as your booking will be cancelled

This module is part of the Social Science Research Methods Centre training programme which is a shared platform for providing research students with a broad range of quantitative and qualitative research methods skills that are relevant across the social sciences.

This workshop introduces students to one of the most frequently used statistics packages for social sciences, R. Students will learn how to download and install R, enter simple data into R, how to load data sets from other statistical packages into R, how to use the R environment for simple calculations, elementary graphs and tables. The module will introduce the use of code for performing these operations. This module is intended primarily for students who have not previously used R and who also do not have much previous experience with statistics. This is not a statistical methods course.

This module is part of the Social Science Research Methods Centre training programme which is a shared platform for providing research students with a broad range of quantitative and qualitative research methods skills that are relevant across the social sciences.

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.

The SSRMC Administrator will make all bookings for this module. If you would like to follow the module you must complete the SSRMC skills audit by 4pm on Thursday 8 October before a place can be booked for you.

If you have already completed the audit you may have had a place booked for you by your Department. Please check this by typing your CRSid into the search box at the very top right of this page, hitting the enter key then clicking on your name. This will show the module(s) you are booked for, as applicable.

This module is part of the Social Science Research Methods Centre training programme which is a shared platform for providing research students with a broad range of quantitative and qualitative research methods skills that are relevant across the social sciences.

This foundational course is for graduate students who have no prior training in statistics.

Topics covered include: the notion of variables and how they are measured; ways of describing the central tendency and the dispersion of a variable; and the principles of hypothesis testing and statistical significance. The course also introduces students to the software R. Each session consists of a lecture part, and a computer lab part with exercises in R.

*DO NOT book for this course if you are already booked for Foundations in Applied Statistics (which includes an introduction to R) as your booking will be cancelled

This module is part of the Social Science Research Methods Centre training programme which is a shared platform for providing research students with a broad range of quantitative and qualitative research methods skills that are relevant across the social sciences.

This workshop introduces students to one of the most frequently used statistics packages for social sciences, R. Students will learn how to download and install R, enter simple data into R, how to load data sets from other statistical packages into R, how to use the R environment for simple calculations, elementary graphs and tables. The module will introduce the use of code for performing these operations. This module is intended primarily for students who have not previously used R and who also do not have much previous experience with statistics. This is not a statistical methods course.

The SSRMC Administrator will make all bookings for this module. If you would like to follow the module you must complete the SSRMC skills audit by 4pm on Thursday 8 October before a place can be booked for you.

If you have already completed the audit you may have had a place booked for you by your Department. Please check this by typing your CRSid into the search box at the very top right of this page, hitting the enter key then clicking on your name. This will show the module(s) you are booked for, as applicable.

This module is part of the Social Science Research Methods Centre training programme which is a shared platform for providing research students with a broad range of quantitative and qualitative research methods skills that are relevant across the social sciences.

This foundational course is for graduate students who have no prior training in statistics.

Topics covered include: the notion of variables and how they are measured; ways of describing the central tendency and the dispersion of a variable; and the principles of hypothesis testing and statistical significance. The course also introduces students to the software R. Each session consists of a lecture part, and a computer lab part with exercises in R.

The SSRMC Administrator will make all bookings for this module. If you would like to follow the module you must complete the SSRMC skills audit by 4pm on Thursday 8 October before a place can be booked for you.

If you have already completed the audit you may have had a place booked for you by your Department. Please check this by typing your CRSid into the search box at the very top right of this page, hitting the enter key then clicking on your name. This will show the module(s) you are booked for, as applicable.

This module is part of the Social Science Research Methods Centre training programme which is a shared platform for providing research students with a broad range of quantitative and qualitative research methods skills that are relevant across the social sciences.

This foundational course is for graduate students who have no prior training in statistics.

Topics covered include: the notion of variables and how they are measured; ways of describing the central tendency and the dispersion of a variable; and the principles of hypothesis testing and statistical significance. The course also introduces students to the software R. Each session consists of a lecture part, and a computer lab part with exercises in R.