Introductory description

This module is targeted toward students interested in a hands-on research project that students will see through from start to finish. In groups students, will choose their own research topic that can be done using a pre-selected high quality UK dataset. They will follow the project process throughout the course from a proposal to a final presentation and research element. The course design will allow students to do real research and practice advanced statistical techniques alongside learning and practicing project management, time management and teamwork. It is ideal for students keen to enhance their quantitative techniques, although suitable for students who may lack quantitative experience but are willing to put in the effort to support the groups quantitative analysis.

Module web page

Module aims

Outline syllabus

This is an indicative module outline only to give an indication of the sort of topics that may be covered. Actual sessions held may differ.

In order to facilitate the acquisition of knowledge and competency, the course is structured and taught via core research project. Students will work together in groups on a hands-on research project that students will see through from start to finish. Groups will choose their own research topic that can be done using a pre-selected high quality UK dataset. This course will allow students to do real research and practice advanced statistical techniques alongside learning and practicing project management, time management, teamwork, and the research process.

In weekly seminars students will participate in themed talks focusing on core skills and research process topics:

• Sample topics include research ethics, defining research questions, understanding dataset methodology, analysing data, interpretation of results and presentation of research findings.

In weekly computer workshops students will have the opportunity to work with their teams on their project under teacher supervision. Where relevant, examples of statistical techniques and data management will also be provided for students to work through either in groups or individually.

Learning outcomes

By the end of the module, students should be able to:

• Demonstrate an understanding of research design, developing research questions and hypotheses and project management
• Demonstrate an understanding of the importance of appropriate data collection, random sampling, and how data collection impacts on the ability to use sample data to make inferences about the broader population
• Interpret, produce, appropriately present, and explain (verbally and in writing) a range of descriptive statistics relevant to research activities
• Demonstrate (verbally and in writing) an understanding of the need for appropriate statistical methods and be able to provide examples of good practice in this subject area
• Interpret, produce, appropriately present, and explain (verbally and in writing) an advanced statistical technique appropriate to the research question, design and data types
• Identify and understand the strengths and limitations of survey data and what it can mean for concepts like causality
• Demonstrate advanced teamworking and meta-cognitive skills in the organization, production and reflection on a research project

Research element

The course is based around a research project using real-world statistical data.

Interdisciplinary

Students will be able to formulate their own research questions using a dataset that spans sociological, psychological, economic, health and education related research themes.

Subject specific skills

• Demonstrate an understanding of the importance of appropriate data collection, random sampling, and how data collection impacts on the ability to use sample data to make inferences about the broader population
• Interpret, produce, appropriately present, and explain (verbally and in writing) an advanced statistical technique appropriate to the research question, design and data types.
• Identify and Understand the strengths and limitations of survey data and what it can mean for concepts like causality

Transferable skills

• Demonstrate an understanding of research design, developing research questions and project management of a research project
• Demonstrate an understanding of the importance of appropriate data collection, random sampling, and how data collection impacts on the ability to use sample data to make inferences about the broader population
• Interpret, produce, appropriately present, and explain (verbally and in writing) a range of descriptive statistics relevant to research activities
  -Demonstrate (verbally and in writing) an understanding of the need for appropriate statistical methods and be able to provide examples of good practice in this subject area
• Interpret, produce, appropriately present, and explain (verbally and in writing) an advanced statistical technique appropriate to the research question, design and data types.
• Identify and Understand the strengths and limitations of survey data and what it can mean for concepts like causality