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SSRMC Training Programme 2014-15

Programme of events provided by Social Sciences Research Methods Centre
(Mon 13 Oct 2014 - Fri 20 Mar 2015)

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Mon 13 Oct 2014 – Wed 29 Oct 2014

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Monday 13 October 2014

14:00
Foundations in Applied Statistics (Series 1) (1 of 4) Finished 14:00 - 16:00 University Information Services, Titan Teaching Room 1, New Museums Site


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 9 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.

16:00
Foundations in Applied Statistics (Series 2) (1 of 4) Finished 16:00 - 18:00 University Information Services, Titan Teaching Room 1, New Museums Site


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 9 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.

Tuesday 14 October 2014

14:00
Survey Research (The Module Formerly Known As 'Designing Surveys') (1 of 4) Finished 14:00 - 15:30 8 Mill Lane, Lecture Room 1

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.

The module aims to provide students with an introduction to and overview of survey methods and its uses and limitations. It will introduce students both to some of the main theoretical issues involved in survey research (such as survey sampling, non-response and question wording) and to practicalities of the design and analysis of surveys. Students who attend this course will be able to evaluate research that uses surveys, in particular to understand issues concerning sample selection, response bias and data analysis; to appreciate and use basic principles of questionnaire design; and to trace appropriate sources of data and appropriate exemplars of good survey practice.

Introduction to R (Series 1) (1 of 4) Finished 14:00 - 16:00 University Information Services, Titan Teaching Room 1, New Museums Site


*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.

16:00
Foundations of Qualitative Methods: Introduction and Overview (1 of 2) Finished 16:00 - 17:30 8 Mill Lane, Lecture Room 1

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.

Wednesday 15 October 2014

14:00
Foundations in Applied Statistics (Series 3) (1 of 4) Finished 14:00 - 16:00 University Information Services, Titan Teaching Room 1, New Museums Site


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 9 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.

Comparative Historical Methods (1 of 4) Finished 14:00 - 15:30 8 Mill Lane, Lecture Room 1

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

Introduction to R (Series 2) (1 of 4) Finished 14:00 - 16:00 University Information Services, Titan Teaching Room 2, New Museums Site


*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.

16:00
Spatial Data Analysis (1 of 8) Finished 16:00 - 18:00 Department of Geography, Downing Site - Large Lecture Theatre

This module is part of the Social Science Research Methods Course 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 introduces students to the capture, display and statistical analysis of spatial data. The first two sessions deal with the construction of a geo-database (using secondary data) and data mapping in a GIS (Geographical Information System). The associated lectures include: descriptions of different spatial data types and spatial objects and a review of spatial data quality issues.

Session three asks what is special about spatial data when undertaking statistical analysis and the associated practical looks at spatial autocorrelation – one of the fundamental properties of spatial data. Session four introduces the principles and some of the methods of exploratory spatial data analysis (ESDA). Session five looks at the topic of cluster or “hot spot” detection (identifying areas of excess risk in the context of disease and crime rates). Session six then considers the special issues that need to be recognized when fitting a regression model (to estimate the association between a dependent variable and a set of independent variables) using spatial data. The course concludes with two special topics – session seven looks at non-parametric methods of spatial interpolation (methods for constructing a map from sampled data) whilst eight looks at areal interpolation (methods for transferring data from one spatial framework to another sometimes referred to as the “change of support problem”).

Each session comprises a one hour lecture followed by a one hour practical class.

Foundations in Applied Statistics (Series 4) (1 of 4) Finished 16:00 - 18:00 University Information Services, Titan Teaching Room 1, New Museums Site


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 9 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.

Monday 20 October 2014

14:00
Foundations in Applied Statistics (Series 1) (2 of 4) Finished 14:00 - 16:00 University Information Services, Titan Teaching Room 1, New Museums Site


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 9 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.

16:00
Foundations in Applied Statistics (Series 2) (2 of 4) Finished 16:00 - 18:00 University Information Services, Titan Teaching Room 1, New Museums Site


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 9 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.

Tuesday 21 October 2014

14:00
Survey Research (The Module Formerly Known As 'Designing Surveys') (2 of 4) Finished 14:00 - 15:30 8 Mill Lane, Lecture Room 1

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.

The module aims to provide students with an introduction to and overview of survey methods and its uses and limitations. It will introduce students both to some of the main theoretical issues involved in survey research (such as survey sampling, non-response and question wording) and to practicalities of the design and analysis of surveys. Students who attend this course will be able to evaluate research that uses surveys, in particular to understand issues concerning sample selection, response bias and data analysis; to appreciate and use basic principles of questionnaire design; and to trace appropriate sources of data and appropriate exemplars of good survey practice.

Introduction to R (Series 1) (2 of 4) Finished 14:00 - 16:00 University Information Services, Titan Teaching Room 1, New Museums Site


*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.

16:00
Foundations of Qualitative Methods: Introduction and Overview (2 of 2) Finished 16:00 - 17:30 8 Mill Lane, Lecture Room 1

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.

Wednesday 22 October 2014

14:00
Foundations in Applied Statistics (Series 3) (2 of 4) Finished 14:00 - 16:00 University Information Services, Titan Teaching Room 1, New Museums Site


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 9 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.

Comparative Historical Methods (2 of 4) Finished 14:00 - 15:30 8 Mill Lane, Lecture Room 1

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

Introduction to R (Series 2) (2 of 4) Finished 14:00 - 16:00 University Information Services, Titan Teaching Room 2, New Museums Site


*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.

16:00
Spatial Data Analysis (2 of 8) Finished 16:00 - 18:00 Department of Geography, Downing Site - Small Lecture Theatre

This module is part of the Social Science Research Methods Course 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 introduces students to the capture, display and statistical analysis of spatial data. The first two sessions deal with the construction of a geo-database (using secondary data) and data mapping in a GIS (Geographical Information System). The associated lectures include: descriptions of different spatial data types and spatial objects and a review of spatial data quality issues.

Session three asks what is special about spatial data when undertaking statistical analysis and the associated practical looks at spatial autocorrelation – one of the fundamental properties of spatial data. Session four introduces the principles and some of the methods of exploratory spatial data analysis (ESDA). Session five looks at the topic of cluster or “hot spot” detection (identifying areas of excess risk in the context of disease and crime rates). Session six then considers the special issues that need to be recognized when fitting a regression model (to estimate the association between a dependent variable and a set of independent variables) using spatial data. The course concludes with two special topics – session seven looks at non-parametric methods of spatial interpolation (methods for constructing a map from sampled data) whilst eight looks at areal interpolation (methods for transferring data from one spatial framework to another sometimes referred to as the “change of support problem”).

Each session comprises a one hour lecture followed by a one hour practical class.

Foundations in Applied Statistics (Series 4) (2 of 4) Finished 16:00 - 18:00 University Information Services, Titan Teaching Room 1, New Museums Site


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 9 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.

Monday 27 October 2014

14:00
Foundations in Applied Statistics (Series 1) (3 of 4) Finished 14:00 - 16:00 University Information Services, Titan Teaching Room 1, New Museums Site


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 9 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.

16:00
Foundations in Applied Statistics (Series 2) (3 of 4) Finished 16:00 - 18:00 University Information Services, Titan Teaching Room 1, New Museums Site


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 9 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.

Tuesday 28 October 2014

14:00
Survey Research (The Module Formerly Known As 'Designing Surveys') (3 of 4) Finished 14:00 - 15:30 8 Mill Lane, Lecture Room 1

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.

The module aims to provide students with an introduction to and overview of survey methods and its uses and limitations. It will introduce students both to some of the main theoretical issues involved in survey research (such as survey sampling, non-response and question wording) and to practicalities of the design and analysis of surveys. Students who attend this course will be able to evaluate research that uses surveys, in particular to understand issues concerning sample selection, response bias and data analysis; to appreciate and use basic principles of questionnaire design; and to trace appropriate sources of data and appropriate exemplars of good survey practice.

Introduction to R (Series 1) (3 of 4) Finished 14:00 - 16:00 University Information Services, Titan Teaching Room 1, New Museums Site


*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.

Wednesday 29 October 2014

14:00
Foundations in Applied Statistics (Series 3) (3 of 4) Finished 14:00 - 16:00 University Information Services, Titan Teaching Room 1, New Museums Site


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 9 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.

Comparative Historical Methods (3 of 4) Finished 14:00 - 15:30 8 Mill Lane, Lecture Room 1

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

Introduction to R (Series 2) (3 of 4) Finished 14:00 - 16:00 University Information Services, Titan Teaching Room 2, New Museums Site


*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.

16:00
Spatial Data Analysis (3 of 8) Finished 16:00 - 18:00 Department of Geography, Downing Site - Small Lecture Theatre

This module is part of the Social Science Research Methods Course 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 introduces students to the capture, display and statistical analysis of spatial data. The first two sessions deal with the construction of a geo-database (using secondary data) and data mapping in a GIS (Geographical Information System). The associated lectures include: descriptions of different spatial data types and spatial objects and a review of spatial data quality issues.

Session three asks what is special about spatial data when undertaking statistical analysis and the associated practical looks at spatial autocorrelation – one of the fundamental properties of spatial data. Session four introduces the principles and some of the methods of exploratory spatial data analysis (ESDA). Session five looks at the topic of cluster or “hot spot” detection (identifying areas of excess risk in the context of disease and crime rates). Session six then considers the special issues that need to be recognized when fitting a regression model (to estimate the association between a dependent variable and a set of independent variables) using spatial data. The course concludes with two special topics – session seven looks at non-parametric methods of spatial interpolation (methods for constructing a map from sampled data) whilst eight looks at areal interpolation (methods for transferring data from one spatial framework to another sometimes referred to as the “change of support problem”).

Each session comprises a one hour lecture followed by a one hour practical class.

Foundations in Applied Statistics (Series 4) (3 of 4) Finished 16:00 - 18:00 University Information Services, Titan Teaching Room 1, New Museums Site


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 9 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.