MEASURING THE SOCIAL WORLD: QUANTITATIVE METHODS - 2022/3
Module code: SOC1050
In light of the Covid-19 pandemic the University has revised its courses to incorporate the ‘Hybrid Learning Experience’ in a departure from previous academic years and previously published information. The University has changed the delivery (and in some cases the content) of its programmes. Further information on the general principles of hybrid learning can be found at: Hybrid learning experience | University of Surrey.
We have updated key module information regarding the pattern of assessment and overall student workload to inform student module choices. We are currently working on bringing remaining published information up to date to reflect current practice during the academic year 2021/22.
This means that some information within the programme and module catalogue will be subject to change. Current students are invited to contact their Programme Leader or Academic Hive with any questions relating to the information available.
This foundation module is design to introduce students to the statistical techniques necessary for implementing and critically evaluating social research. Emphasis will be put on when and how data is collected, how to use basic statistical techniques to analyse the data appropriately, and how to interpret results, rather than on theoretical derivations. A familiarity with R will also be acquired during practical work.
BERLUSCONI Giulia (Sociology)
Number of Credits: 15
ECTS Credits: 7.5
Framework: FHEQ Level 4
JACs code: G300
Module cap (Maximum number of students): N/A
Overall student workload
Independent Learning Hours: 95
Lecture Hours: 22
Laboratory Hours: 11
Captured Content: 22
Prerequisites / Co-requisites
Indicative content includes:
• The role of statistics in modern societies;
• The ethics of quantitative research;
• Surveys and questionnaire design;
• Sampling theory and practice;
• Levels of measurement and types of variable;
• Estimators of central tendency and dispersion;
• Statistical inference, estimation and hypothesis testing.
|Assessment type||Unit of assessment||Weighting|
|School-timetabled exam/test||TEST (1 HOUR)||40|
|Examination||SHORT ANSWER AND MCQ EXAM (1 HOUR)||60|
The assessment strategy is designed to provide students with the opportunity to demonstrate that they have (a) understood the basic concepts used to describe the characteristics of population and survey data, and (b) know how to choose appropriate statistical techniques to test hypotheses and interpret the associated statistical outputs.
The summative assessment for this module consists of a one-hour class test on descriptive statistics, and a one-hour exam on hypothesis testing.
The formative assessment includes verbal feedback in class, when students will have the opportunity to work on class exercises and receive feedback on how they are progressing.
- Introduce students to the statistical techniques required to conduct and critically evaluate social research
- Provide an understanding of when and how to use particular statistical techniques, including hand on experience with R
- Offer a conceptual and theoretical outline of inferential statistics
|001||Design a quantitative study, collect relevant data, and analyse them using univariate and bivariate statistical tehniques|
|002||Have an understanding of the use of computer software for statistical analysis||PT|
|003||Have a thorough grounding in descriptive and basic inferential statistical techniques|
C - Cognitive/analytical
K - Subject knowledge
T - Transferable skills
P - Professional/Practical skills
Methods of Teaching / Learning
The learning and teaching strategy is designed to encourage students to understand the importance of using statistics in social research as a way of describing and explaining social life.
The learning and teaching methods include:
• Lectures based around the theoretical and practical importance of statistics and how they are commonly applied to social research;
• Laboratory classes where students will familiarise themselves with the technical and practical issues using R to analyse quantitative data.
Indicated Lecture Hours (which may also include seminars, tutorials, workshops and other contact time) are approximate and may include in-class tests where one or more of these are an assessment on the module. In-class tests are scheduled/organised separately to taught content and will be published on to student personal timetables, where they apply to taken modules, as soon as they are finalised by central administration. This will usually be after the initial publication of the teaching timetable for the relevant semester.
Upon accessing the reading list, please search for the module using the module code: SOC1050
Programmes this module appears in
|Media and Communication BSc (Hons)||2||Compulsory||A weighted aggregate mark of 40% is required to pass the module|
|Criminology BSc (Hons)||2||Compulsory||A weighted aggregate mark of 40% is required to pass the module|
|Criminology and Sociology BSc (Hons)||2||Compulsory||A weighted aggregate mark of 40% is required to pass the module|
|Sociology BSc (Hons)||2||Compulsory||A weighted aggregate mark of 40% is required to pass the module|
Please note that the information detailed within this record is accurate at the time of publishing and may be subject to change. This record contains information for the most up to date version of the programme / module for the 2022/3 academic year.