• Offered for Year: 2024/25

• Module Leader(s): Dr Chris Moreh
• Co-Module Leader: Dr Lauren Ackerman
• Lecturer: Dr Jen Tarr

• Owning School: School X
• Teaching Location: Newcastle City Campus

Semesters

Your programme is made up of credits, the total differs on programme to programme.

Aims

This module aims to develop students’ understanding of the general principles of quantitative data analysis, in addition to training them in the use of a statistical software package.
- Students will be introduced to the concepts underlying the statistical analysis of quantitative data in the social sciences and humanities;
- Students will develop a critical understanding of the statistical methods they learn about;
- Students will learn about and use a common statistical software package.

Outline Of Syllabus

The module will begin and end with sessions that set out the importance of developing a critical understanding of statistics and of quantitative research more broadly. Data management and data visualisation will also be discussed. Students will then follow one of two pathways.

The Introductory pathway is suitable for those with little to no prior experience with quantitative methods and introduces key concepts such as variables and descriptive statistics before moving on to inferential statistics and introducing basic statistical tests for two variables including comparing means, correlation and linear regression.

The Intermediate pathway is suitable for students who have an understanding of the topics covered in the Introductory pathway, and covers more advanced modes of regression analysis and the generalised linear model.

Teaching Methods

Teaching Activities

Teaching Rationale And Relationship

The module uses a mix of live lectures, practical computer labs and/or online blended materials which students will work through at their own pace. The emphasis of the module will be on the development of practical skills in applying quantitative data analysis, as well as development of critical awareness of quantitative methods. Blended materials will include statistical software training via online videos as well as supervised computer lab sessions.

Assessment Methods

The format of resits will be determined by the Board of Examiners

Other Assessment

Formative Assessments

Formative Assessment is an assessment which develops your skills in being assessed, allows for you to receive feedback, and prepares you for being assessed. However, it does not count to your final mark.

Assessment Rationale And Relationship

Students will have the option to choose between a critical analysis of published studies, or a data analysis assignment on a topic of their own choosing. The module aims to encourage students to engage weekly with the material, acknowledging the fact that the methods, concepts and skills introduced build on each other in a scaffolded way. Accordingly, students will be encouraged to develop a scaffolded portfolio that culminates in a report to be submitted for summative assessment at the end of the semester.
The portfolio consists of weekly brief reports - critical reflections or data analysis and interpretation - which students can submit for formative feedback. Formative feedback may take the shape of self-grading, peer discussion, or in-class feedback from the instructors. Developing the weekly reports falls within the skills practice and assessment preparation and completion activities as part of the guided independent study hours.
The assessment aims to develop practical skills in reading and producing quantitative analyses, as well as the ability to critically evaluate quantitative research. Some specific details of the assessment will vary depending on the pathway.

Reading Lists

• HSS8005's Reading List

Timetable

• Timetable Website: www.ncl.ac.uk/timetable/
• HSS8005's Timetable