Data Analytics and Social Statistics (Online)

Entry requirements

An Upper Second (2:1) class honours degree, or the overseas equivalent in a social science discipline.

We may also consider exceptional applicants with a Lower Second (2:2) class honours degree in a social science discipline (or the overseas equivalent), with either research experience or equivalent professional background.

Months of entry

September

Course content

Our online Data Analytics and Social Statistics course is designed for professionals working with big and social data across various sectors. It covers the entire data lifecycle, from collection to presentation, using popular methods like machine learning and structural equation modelling. By leveraging real-world data and R software, you'll gain practical skills applicable to diverse fields.

Course unit overview

Core units:

• Data Cleaning and Visualization Using R: Develops skills in data cleaning, manipulation, and visualization using R and RStudio.
• Introduction to Statistical Modelling: Introduces foundational statistical concepts and techniques for analysing social science data.
• Survey Methods and Online Research: Covers the principles of survey design, data collection, and analysis, including ethical considerations.
• Data Science Modelling: Explores advanced data science techniques, such as machine learning and predictive modelling, for analysing large and complex datasets.
• Multilevel and Longitudinal Analysis: Focuses on analysing hierarchical and time-series data, including complex survey designs.
• Research Skills in Practice: Develops essential research skills, including literature review and hypothesis formulation.

Optional units:

• Demographic Forecasting: Covers methods for analysing population trends and forecasting future demographic patterns.
• Structural Equation Modelling: Introduces advanced statistical modelling techniques for analysing complex relationships between variables.

Dissertation:

• Project: Students undertake a significant research project involving data analysis, interpretation, and presentation of findings.

Benefits to your career

• Develop the skills to advance your career in various industries, including public policy, market research, education, and non-profit organisations.
• Gain the necessary knowledge and skills to transition into a career in social data analytics.
• Enhance your understanding of statistical methods and their application in social sciences.
• Learn about ethical considerations in data handling, develop critical thinking skills to evaluate research, and gain practical experience in data collection, analysis, and visualisation.
• Learn to design and conduct independent research projects using advanced quantitative methods.
• Study with a world-class institution recognized for its quality education.

Where and when you will study

This course is 100% online, allowing you to study with The University of Manchester from anywhere in the world. You can learn flexibly at a time and pace that suits you. You will gain access to the University’s quality teaching, benefiting from the expertise and reputation of our School of Social Sciences, ranked 5th in the UK (The Times Higher Education Guide 2022).

All course material is available through the virtual learning environment (VLE) and includes video, assessments, workbooks and more. You will also benefit from interactive teaching and the chance to collaborate with your course peers from your global community.

Fees and funding

Please view the course overview page on The University of Manchester website for more details of fees, plus any scholarships and bursaries applicable for this course. Application discount and Alumni discount are available.