Please note: there may be some adjustments to the teaching arrangements published in the course catalogue for 2020-21. Given current circumstances related to the Covid-19 pandemic it is anticipated that some usual arrangements for teaching on campus will be modified to ensure the safety and wellbeing of students and staff on campus; further adjustments may also be necessary, or beneficial, during the course of the academic year as national requirements relating to management of the pandemic are revised.

QM1 - Measuring Your Social World SPS1001

  • Academic Session: 2020-21
  • School: School of Social and Political Sciences
  • Credits: 20
  • Level: Level 1 (SCQF level 7)
  • Typically Offered: Semester 1
  • Available to Visiting Students: Yes
  • Available to Erasmus Students: Yes

Short Description

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.

Timetable

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.

Requirements of Entry

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

Excluded Courses

Statistics 1A

Co-requisites

None.

Assessment

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. The first three problem sets will involve the students using R to carry out statistical tests associated with the course material and will be distributed at pre-specified intervals throughout the semester (each contributing 10% towards the lab book mark). The final problem set will be in essay format in the form of a critical analysis (contributing 70% towards the final mark). The essay will be 1500 words long. The essay component will be based on an actual data set and a fabricated media report. Students must analyse the data to establish which elements of the media report are fabricated or distorted. The marked work is their review of the media report, and justification for their arguments comes from how well they use the 'evidence' that they've analysed.

 

The exam will last for 2 hours and be in four parts: The first around interpretation will use an 'Ugly Graph' scenario using real charts exported from peer reviewed journals. Students will be asked to

1: discuss the aspects that prevent the graph or table from conveying its story clearly; outlining what is wrong and 2: what would you do to fix it. The assignment will test knowledge of various statistics and what they are meant to tell us, their ability to read data visualisations and deduce what the story is, and help facilitate their practice in presenting material in a clear manner (which is not an easy task). 

In the other part of the exam students will be examined on how well they understand core concepts of quantitative methods. One section will address levels of measurement and basic concept definitions. Another section will involve the discussion of data set management. The final section will present students with information covered in the class and asked to explain various components of statistical analysis. The information will include R output tables that students would have been previously exposed to in labs and lectures.

Main Assessment In: December

Course Aims

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.

Intended Learning Outcomes of Course

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).

■ Demonstrate the ability to perform basic quantitative data analysis using principles of inference on secondary data sets using SPSS.

Note: additional information about the course content and timetable is available from the document attached 'QM1 & 2 course overview and proposed timetable'.

Minimum Requirement for Award of Credits

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).