Social Sciences Research Methods Programme course timetable
Tuesday 3 December 2019
14:00 |
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:
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. |
Wednesday 4 December 2019
10:00 |
Doing Multivariate Analysis (DMA-3)
Finished
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. |
Doing Multivariate Analysis (DMA-2)
Finished
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. |
|
14:00 |
Doing Multivariate Analysis (DMA-2)
Finished
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. |
16:00 |
Doing Multivariate Analysis (DMA-3)
Finished
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. |
Friday 17 January 2020
10:00 |
Doing Multivariate Analysis (DMA-1)
Finished
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)
Finished
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)
Finished
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-2)
Finished
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. |
Monday 20 January 2020
10:00 |
Doing Multivariate Analysis (DMA-1)
Finished
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)
Finished
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)
Finished
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 |
Research Ethics
Finished
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. |
16:00 |
Doing Multivariate Analysis (DMA-2)
Finished
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. |
Tuesday 21 January 2020
14:00 |
Introduction to R
Finished
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:
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''' |
16:00 |
Conversation and Discourse Analysis
Finished
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:
|
Wednesday 22 January 2020
14:00 |
Introduction to R
Finished
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:
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''' |
Monday 27 January 2020
09:00 |
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:
|
13:00 |
Ethics in Data Collection and Use
Finished
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. |
14:00 |
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:
|
Tuesday 28 January 2020
14:00 |
Introduction to Stata
Finished
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 SSRMC. You will learn:
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. |
16:00 |
Conversation and Discourse Analysis
Finished
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:
|
Wednesday 29 January 2020
09:00 |
This module follows on from Foundations in Applied statistics, and will teach you the basics of common bivariate techniques (that is, techniques that examine the associations between two variables). 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 apply these techniques to the analysis of real data. Techniques to be covered include:
For best results, students should expect to do a few hours of private study and spend a little extra time in the computer labs, in addition to coming to class. |
14:00 |
This module follows on from Foundations in Applied statistics, and will teach you the basics of common bivariate techniques (that is, techniques that examine the associations between two variables). 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 apply these techniques to the analysis of real data. Techniques to be covered include:
For best results, students should expect to do a few hours of private study and spend a little extra time in the computer labs, in addition to coming to class. |
Monday 3 February 2020
14:00 |
This short two-hour course will provide an introduction to measurement issues in the social sciences. We design questions (or "survey instruments") to gain information on the concepts we are researching. Two prime considerations in whether an instrument is effective are validity (does our instrument actually measure what we want it to measure?) and reliability (does our instrument give consistent results across a range of different situations?) Considerations of validity and reliability are important across many areas of social science, including the measurement of personality and mental health; attitudes; ability tests; substance use disorders; and cultural differences and similarities between various groups. The course will discuss the importance, concepts, and types of validity and reliability. We will also briefly look at some statistical techniques for validity and reliability checks: Cronbach’s Alpha, Kappa coefficient, and Factor Analysis. |