SC385-6-AU-CO:
Models and Measurement in Quantitative Sociology

The details
2021/22
Sociology and Criminology
Colchester Campus
Autumn
Undergraduate: Level 6
Current
Thursday 07 October 2021
Friday 17 December 2021
15
08 October 2021

 

Requisites for this module
SC203 or GV200 or GV207 or SC208
(none)
(none)
(none)

 

(none)

Key module for

(none)

Module description

The first term of the module is focused on statistical models and begins with simple OLS regression and provides a framework for modelling strategy and variable selection. Students are then taken through extensions to the basic OLS model, with categorical predictors, interactions and non-linear terms. Next, we introduce models for categorical outcomes: binary logistic and multinomial logit. The term concludes with a discussion of practical topics in survey data analysis – how to deal with complex sample designs, weighting and non-response adjustments. The modelling framework outlined in this term builds the foundations for advanced quantitative social science methods.

Case studies from social sciences (e.g., decision making in criminal justice, censorship and collective action, social networks and public health) will be used throughout the course to provide synergy between sociological issues, statistical techniques, and data analysis. The students will engage with data-driven exercises, which they will consolidate in research portfolios demonstrating their data science accomplishments in the domain of sociology as well as employability skills.

Module aims

This module will develop students' understanding of quantitative analysis and impart the practical skills necessary for carrying out advanced statistical analysis of social data using modern statistical software.

Module learning outcomes

By the end of course students should be able to:

understand the principles and practice of statistical modelling
critically evaluate research articles that use statistics
understand the link between substantive theory, measurement and statistical models
carry out intermediate and advanced statistical analysis using SPSS and other software

Module information

If you wish to take this module but have not taken the second year module 'Researching Social Life II' (SC203-5-FY), please contact the module supervisor to see if you have the appropriate background in statistics.

Please click on the link below to view the Introduction video to SC385 Models and Measurement in Quantitative Sociology

https://moodle.essex.ac.uk/mod/page/view.php?id=668576

Learning and teaching methods

As there are still restrictions related to COVID-19 in place, some of the teaching on most modules will take place online. Most modules in Sociology are divided into lectures of around 50 minutes and a class of around 50 minutes. Some are taught as a 2hr seminar, and others via a 50-minute lecture and 2-hr lab. For the majority of modules the lecture-type content will be delivered online – either timetabled as a live online session or available on Moodle in the form of pre-recorded videos. You will be expected to watch this material and engage with any suggested activities before your class each week. Most classes labs and seminars will be taught face-to-face (assuming social distancing allows this). Please note that you should be spending up to eight hours per week undertaking your own private study (reading, preparing for classes or assignments, etc.) on each of your modules (e.g. 32 hours in total for four 30-credit modules). The lectures provide an overview of the substantive debates around the topic of the week, while the classes will give you the opportunity to reflect on your learning and actively engage with your peers to develop your understanding further. The weekly classes will take place face-to-face (unless there is a change in the current COVID safety measures). You are strongly encouraged to attend the classes as they provide an opportunity to talk with your class teacher and other students. The classes will be captured and available via Listen Again. However, if you want to gain the most you can from these classes it is very important that you attend and engage. Please note that the recording of classes is at the discretion of the teacher.

Bibliography

This module does not appear to have a published bibliography for this year.

Assessment items, weightings and deadlines

Coursework / exam Description Deadline Coursework weighting
Coursework   Online Quiz    30% 
Coursework   Data Analysis Report    70% 

Exam format definitions

  • Remote, open book: Your exam will take place remotely via an online learning platform. You may refer to any physical or electronic materials during the exam.
  • In-person, open book: Your exam will take place on campus under invigilation. You may refer to any physical materials such as paper study notes or a textbook during the exam. Electronic devices may not be used in the exam.
  • In-person, open book (restricted): The exam will take place on campus under invigilation. You may refer only to specific physical materials such as a named textbook during the exam. Permitted materials will be specified by your department. Electronic devices may not be used in the exam.
  • In-person, closed book: The exam will take place on campus under invigilation. You may not refer to any physical materials or electronic devices during the exam. There may be times when a paper dictionary, for example, may be permitted in an otherwise closed book exam. Any exceptions will be specified by your department.

Your department will provide further guidance before your exams.

Overall assessment

Coursework Exam
100% 0%

Reassessment

Coursework Exam
100% 0%
Module supervisor and teaching staff
Prof Nick Allum, email: nallum@essex.ac.uk.
Professor Nick Allum
Jane Harper, Undergraduate Administrator, Telephone: 01206 873052 E-mail: socugrad@essex.ac.uk

 

Availability
Yes
Yes
Yes

External examiner

Dr Jennifer Fleetwood
Goldsmiths, University of London
Senior Lecturer in Criminology
Resources
Available via Moodle
Of 33 hours, 14 (42.4%) hours available to students:
19 hours not recorded due to service coverage or fault;
0 hours not recorded due to opt-out by lecturer(s), module, or event type.

 

Further information
Sociology and Criminology

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