03
October
2022
|
13:55
Europe/London

New Manchester master’s course will boost data literacy, help fight fake news and disinformation

The University of Manchester has launched a new postgraduate degree aimed at developing data analysis experts to help in the continuing fight against disinformation and fake news.

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The new Data Analytics and Social Statistics master’s degree will begin in September 2023 and promises to be a pioneering course that prioritises data veracity and analysis.

Dr Alexandru Cernat, Course Director, Senior Lecturer in the Department of Social Statistics and the chair of the Social Statistics Section of the Royal Statistical Society, says:

“In a time of disinformation campaigns, this master’s is well-placed to promote data literacy and inform the next generation of data scientists with the skills to tackle such issues.

This master’s will enable students to confidently analyse real-world data by using the latest statistical software and methods. The course covers all the stages of working with data from data collection, importing, wrangling and visualisation to analysis and presentation.”

As data continues to improve in scope and specificity, we need to develop the next generation of data scientists to harness this information effectively and create actionable insights that will improve our world. 

The course was developed to help address key world challenges, such as inequality and data privacy, and to produce impact in various contexts including policymaking, education, healthcare, medicine and voluntary work.

Dr Ioana Macoveciuc, Lecturer in Social Statistics, says: “Using real-world social data can really make a big impact in terms of social problems. It helps with bigger picture, if more people understand the context of the data and how it’s used, people can create an impact.”

The new Master’s in Data Analytics and Social Statistics was designed with these issues at the forefront and with the need to combat fake news and disinformation in mind. Students will be taught by experts in social sciences and data sciences, working with real-world data in this highly practical course.

Tailored for busy working professionals, this master’s is 100% online, allowing students to easily fit it into their schedules amongst their other commitments. Aimed at individuals from industries as wide as education, health, business analytics and non-profits, this course will empower students to leverage data for predictive purposes.

Prospective students will also be able to apply for an Equity and Merit Scholarship, created to promote the United Nations Sustainable Development Goals. These scholarships are open to applicants from Ethiopia, Malawi, Tanzania, Uganda and Zimbabwe with the potential to deliver solutions to encourage sustainable development.

Based firmly in practical techniques such as data analysis using R, students already working within data analysis will be able to apply their learning directly into their daily work. Newcomers to the field will be able to upskill and use this degree as a conversion to a new career.

Topics covered in this course include data visualisation, statistical modelling, survey methods, research skills and more.

This course was specifically designed to help expand data literacy and encourage students to question the purpose of how statistics are presented and why. The context of data, including how it is used, is a key focus.

With the dissertation, students on this course can focus on a contemporary research topic of interest to showcase their quantitative and analytical skills. Students will be taught by researchers who conduct these activities in their professional work, further enhancing the practical and real-world dimension of the course.

Dr Alexandru Cernat comments:

“The dissertation will help bring all these skills together to create an analytics report or research paper that answers real-world problems using advanced statistical methods and complex data.”

The first class will begin in September 2023. Learn more about the new postgraduate course in Data Analytics and Social Statistics.

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