Introductory description

The module will allow students to gain an insight into the principles, challenges, and applications of statistical consulting. It will equip them with a skill set to become effective statistical consultants, including problem-solving and communication skills. Students will work across multiple disciplines, selecting and applying a variety of statistical methods and tools to address practical problems, and will communicate to various audiences (including non-specialists) the outputs. Students will work with others to develop and present solutions to complex and often ill-defined problems.

Prerequisites (Undergraduates) Students taking this module will need knowledge from following modules:

• ST404-15 Applied Statistical Modelling.

Students taking this module will find that it has synergies with the following modules:

• ST301-15 Bayesian Statistics and Decision Theory, or ST413 Bayesian Statistics and Decision Theory with Advanced Topics;
• ST323-15 Multivariate Statistics or ST412 Multivariate Statistics with Advanced Topics;
• ST344-15 Professional Practice of Data Analysis;
• ST346-15 Generalised Linear Models for Regression and Classification.

Students must be comfortable working with others in a collaborative and constructive manner.

Prerequisites (Taught postgraduates) Students taking this module will need knowledge from following modules:

• ST961 Statistical Methods and Practice
• ST962 Advanced Topics in Statistics and Probability

Students taking this module will find that it has synergies with the following modules:

• ST412 Multivariate Statistics with Advanced Topics;
• ST413 Bayesian Statistics and Decision Theory with Advanced Topics;

Students must be comfortable working with others in a collaborative and constructive manner.

Software prerequisites. It is expected that those taking the module will be able to autonomously and independently use R and other relevant software.

This module is not available as an unusual option.

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.

The module will serve as an incubator for students to act as statistical consultants and will help in the acquisition of
practical skills needed for consulting, including effective communication, teamwork, critical thinking, and problem-solving. The module provides students with the opportunity to apply their theoretical knowledge and skills to practical problems, and thus helps in the preparation for a future career in data science, statistical forensics and work with those in industry. Consequently, there will be the need to work with others confidently and constructively, often in time-constrained situations.
The specific topics covered in the module will vary depending on the consulting projects.

Learning outcomes

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

• Select and apply appropriate statistical techniques and methods to analyse and interpret data
• Communicate complex statistical concepts and findings to a range of audiences
• Use statistical software to conduct data analysis and assess the usage of different software packages
• Identify the different stages of team development and define responsibilities within a team
• Apply critical thinking and problem-solving skills to address practical statistical challenges and make evidence-based recommendations.

Research element

This module contains a research component as students might need to seek and combine information from various sources, may be required to review and analyse existing literature, critically evaluate research methodologies in published studies, adapt and combine in a creative way various methodologies to new contexts.

Interdisciplinary

Depending on the particular consultancy undertaken the module might incorporate an interdisciplinary component, as consulting may involve working with clients from different disciplines and applying statistical methods in various domains.

International

Depending on the particular consultancy undertaken the module might contain some international element, for instance working with and analysing datasets collected from international sources, or even addressing statistical challenges related to cross-cultural research.

Subject specific skills

• Ability to understand and analyse datasets, and to identify potential issues with data quality.

• Ability to work in collaboration with potential clients, to understand their objectives, to apply appropriate statistical methodology, and to provide appropriate recommendations.

• Use statistical software appropriately and effectively.

• Use various statistical models, approaches, theories, and techniques, while being aware of their underlying assumptions and limitations.

• Communicate effectively statistical concepts, methodologies and findings to non-experts, presenting results in a clear and concise manner, using appropriate visualisations and explanations.

• Discuss and critique own and the work of peers.

Transferable skills

• Communication skills: ability to clearly communicate statistical concepts and findings to non-technical stakeholders.

• Collaboration, teamwork and interpersonal skills.

• Project management, managing one’s time, respecting deadlines, setting priorities and managing expectations.

• Understanding ethical guidelines and regulations, e.g. related to data privacy, confidentiality, and responsible data use.

• Adaptability: ability to adapt to different contexts, learn and apply statistical methods to new domains.

• Continuous learning and development: willingness to continuously update one’s skillset and knowledge is valuable for the future careers of the students, as the fields of statistics and data science are constantly evolving.

• Confidence in contributing to the discussions within larger groups in a small conference/workshop environment.