Course Catalogue

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Students will work through basic quantitative techniques and learn how they can apply these to understanding the social world around them with specific focus on data available for public consumption: produced by the State and presented in the media. The course will introduce students to key datasets and relevant readings that link to the school's subject areas and will include topical questions related to key themes: inequality, welfare, crime, conflict and health.

10 x 1 hour lectures during a 10 week semester - lecture led.

Likely to be Monday 10-11am.*

10 x 1 hour taught labs during a 10 week semester - lecture led.

Likely to be Mondays 12pm-1pm, 1pm-2pm, 2pm-3pm * (labs can accommodate up to 33 people, course is capped at 99)

10 x 1 hour supervised labs during a 10 week semester - GTA led.

Likely to be Wednesday 11am-12pm, 12pm-1pm or a Thursday 10-11 * (labs capped at 33)

*All level 1 and level 2 lectures in SSPS have been mapped and the above represents gaps in timetables so that all students are able to elect to study for a 'with' degree.

Commensurate with other Level 1 courses offered in the SSPS and supported with blended learning via the VLE Moodle.

Mandatory entry requirements in line with those generally required by the MA (Social Sciences) degree programme.

Statistics 1A

None.

Students will submit a lab book at the end of the semester that will contain 4 problems based on the material covered throughout the semester. Each piece within the lab book will retain is weighted (Assignments 1-3 are worth 20% of the lab book and assignment 4 is worth 40% of the lab book). This will mean labs 1-3 will be worth 15% of the final grade and assignment 4 will be worth 30% of the final grade for the course. Note that each lab book assignment receives its own mark means that not all pieces would need to be completed to achieve the 75% submission of course work to receive a grade for the course.

The presentation, worth 25% of the final course grade (this had been discussed with our external examiner who agreed that exams were not optimal for measuring comprehension and mastery of the material) includes the following elements:

• Be 5-10 minutes long pre-recorded presentation

• Introduce a skill covered in the course

• Provide explanation of why/when the skill is used

• Demonstrate how to execute/use the skill (by hand and/or with software)

• Explain how to interpret findings

• Offer a real-life example of how/when to use

• Assign a task related to the skill

The presentation can be pre-recorded and submitted, or in exceptional circumstances live via a zoom meeting, where the marker will record the presentation for second marking/moderation purposes. 

In keeping with the Accessibility and Inclusive Learning Policy of the School accommodations to the presentation can be made for students with disabilities that hinder attendance and/or public speaking.

The aims of this course are:

■ To offer students an introduction to using quantitative methods as a means to understanding the social world around them through the analysis of key overarching themes common to social science subject areas.

■ To develop a critical view of data published in a variety of sources including State and Media data.

■ To equip students with introductory quantitative and analytical skills to evaluate the data that they are exposed to, and to critically reflect on the impact of this data on social issues and policy formation.

By the end of this course students will be able to:

■ Demonstrate a critical awareness of the way quantitative knowledge is used to inform social science debates; including information published by both State and Media sources.

■ Show an introductory understanding of quantitative literacy (for example reading and interpreting summary data including data visualisations) and ability to produce summary data (including data visualisations).

■ Perform basic quantitative data analysis using principles of inference on secondary data sets using R.

Students must submit at least 75% by weight of the components (including examinations) of the course's summative assessment.

Students must regularly attend and participate in lectures, taught and supervised labs; undertake all aspects of the course work (including formative and summative assignments).