SSRMC Training Programme 2013-14

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 module aims to provide students with an overview of survey methods, uses and limitations; to introduce students to the practicalities of design and use of surveys; to examine complexities of question and answer process; to examine practicalities of survey sampling and response.

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.

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

It introduces students to the basic general concepts that underlie descriptive and inferential statistics. Topics covered include the notion of variables and how they are measured; ways of describing the central tendency and dispersion of a variable; basic idea of sampling and statistical inference; and principles of hypothesis testing and statistical significance.

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.

Introducing students to the general philosophical debates concerning scientific methodology; assessing their ramifications for the conduct of qualitative social research. 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.

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.

An introduction to comparative historical research methods, emphasising their qualitative dimensions.

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.

Writing an empirical chapter or conference paper can be a daunting experience before learning how to properly translate quantitative results into figures and words. This course is aimed at teaching students how to present and describe quantitative research data in the correct academic format. No prior training in statistics is required, as general concepts relating to descriptive and inferential statistics, the main focus of the course, will be reviewed.

This course will cover how to: choose the right table or graph to present descriptive and inferential statistics [session 1]; properly and effectively present graphs, tables, and figures from raw data, R, and SPSS output [session 2]; write text to accompany the numbers in proper academic format [session 3]; and format or write according to the APA (American Psychological Association) or MLA (Modern Language Association) strict guidelines of academic publication [session 4].

In addition to lectures and out-of-class readings, this course utilizes several practical exercises to help students learn how to select, format, and describe tables and figures based upon specific types of quantitative data.

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 eligible graduate students who have no prior training in statistics.

It introduces students to the basic general concepts that underlie descriptive and inferential statistics. Topics covered include the notion of variables and how they are measured; ways of describing the central tendency and dispersion of a variable; basic idea of sampling and statistical inference; and principles of hypothesis testing and statistical significance.

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 module aims to provide students with an overview of survey methods, uses and limitations; to introduce students to the practicalities of design and use of surveys; to examine complexities of question and answer process; to examine practicalities of survey sampling and response.

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.

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

It introduces students to the basic general concepts that underlie descriptive and inferential statistics. Topics covered include the notion of variables and how they are measured; ways of describing the central tendency and dispersion of a variable; basic idea of sampling and statistical inference; and principles of hypothesis testing and statistical significance.

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.

Introducing students to the general philosophical debates concerning scientific methodology; assessing their ramifications for the conduct of qualitative social research. 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.

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.

An introduction to comparative historical research methods, emphasising their qualitative dimensions.

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.

Writing an empirical chapter or conference paper can be a daunting experience before learning how to properly translate quantitative results into figures and words. This course is aimed at teaching students how to present and describe quantitative research data in the correct academic format. No prior training in statistics is required, as general concepts relating to descriptive and inferential statistics, the main focus of the course, will be reviewed.

This course will cover how to: choose the right table or graph to present descriptive and inferential statistics [session 1]; properly and effectively present graphs, tables, and figures from raw data, R, and SPSS output [session 2]; write text to accompany the numbers in proper academic format [session 3]; and format or write according to the APA (American Psychological Association) or MLA (Modern Language Association) strict guidelines of academic publication [session 4].

In addition to lectures and out-of-class readings, this course utilizes several practical exercises to help students learn how to select, format, and describe tables and figures based upon specific types of quantitative data.