IP306 Quantitative Methods: Research Project

Module leader: Dr Lauren Bird

Optional module

15 CATS

Term 2

10 weeks

Moodle Platform »

Important information

This module is no longer running in the academic year 2021-22.

Prerequisites

SO130 or IP110
IP309 (recommended)

Students with other backgrounds will be admitted on a case-by-case basis, though it is expected that they will have an equivalent level knowledge as students who have studied the conventional prerequisites. Please contact the module leader for further information.

Principal Aims

This module is for you if you are interested in a hands-on research project to see through from start to finish. In groups, students will choose a 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.

To achieve its aims, the module balances the necessary technicality of statistical analysis with enhanced learning in research processes and project design.

Through extensive hands-on use of a real-world dataset, students gain research skills, core statistical knowledge, and a transferable toolkit of practical analytical, team, research and project management skills required for a variety of post course experiences either in further studies or work.
The module is taught via a combination of lecturer-led classroom discussions, group work and problem-based learning, and practical computer lab sessions.

The module is taught via a combination of lecturer-led classroom discussions, problem-based learning, and practical computer lab sessions.

Principal Learning Outcomes

Upon completion of this module, you will 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

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.

Assessment Skills

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.

Employability Skills

Through this module, you will develop different skills that are sought by employers which will support your professional development. We have highlighted this to enable you to identify and reflect on the skills you have acquired and apply them throughout your professional journey including during the recruitment process whether this is in a CV/application form or at an interview.

Data analysis: Qualitative and quantitative analysis techniques and evaluation methods using tools such as Excel, STATA.
Teamwork: Collaborating with peers and multiple partners on project briefs involving sharing ideas, knowledge and best practice.
Time and self-management: Developed through planning and managing weekly tasks, working towards agreed group schedules, as well as on your own initiative without supervision.
Research: Developed through carrying out research using sample real-world data involving formulating research questions, conducting literature reviews, identifying appropriate measurement variables, and analysing and interpreting results. Additionally, writing and communicating the research in an appropriate manner.
Project management and organisation: Working on a project involving all stages from the initial problem identification through planning, research, analysis, scheduling tasks, monitoring progress to completion.

Please note: Module availability and staffing may change year on year depending on availability and other operational factors. The School for Cross-faculty Studies makes no guarantee that any modules will be offered in a particular year, or that they will necessarily be taught by the staff listed on these pages.