To apply please refer to the Essex Summer School webpages.

Please note that the deadline for applications is 5 March 2025. 

A. Foundations of Data Literacy (Modules 1-3)

Build essential skills for working with data, including concepts, basic analysis, and effective reporting. These modules are based on instruction in Microsoft Excel. No previous background is needed.
Module 1 (April 10 & 11): Data Skills Foundations
Covering essential concepts for working with data in Excel.
Module 2 (April 16 & 17): Data Analysis and Interpretation
A first introduction to data analysis, including Excel fundamentals and basic statistics.
Module 3 (April 24 & 25): Communicating with Data
Develop skills in creating effective visualisations and presenting data-driven stories.

B.   Introduction to Data Analysis in R (Modules 4-6)

Learn the basics of the powerful R statistical programming environment, along with the fundamentals of data manipulation and analysis. Course A is not required but recommended for those with no previous experience in data analysis.  
Module 4 (May 1 & 2): Introduction to the R Environment
Get started with R programming through hands-on practice and basic data operations. 
Module 5 (May 8 & 9): Data Manipulation with R
Learn data transformation and validation techniques to prepare data for analysis.
Module 6 (May 15 & 16): Basic Statistical Analysis in R
Apply statistical methods and create professional visualisations. 

C. Intermediate Statistics with R (Modules 7-9)

Intended for those who have taken course B above, these modules take your data skills to the next level with intermediate statistics using the R environment and more advanced visualisation, modelling, text processing, and automated reporting techniques. 
Module 7 (June 5, 6): Data Visualisation with R
Create advanced visualisations and interactive graphics using specialised R packages.
Module 8 (June 12, 13): Data Analysis and Modelling in R
Explore regression analysis, time series, and predictive modelling techniques.
Module 9 (June 19, 20): Advanced Data Types and Reporting Workflows in R
Master automated reporting and interactive dashboards using R Markdown.

Each module is scheduled to run from 10 am to 5 pm on the date specified.

Full details on module content can be found on the Essex Summer School webpages

Foundations of Data Literacy (Modules 1-3) equips participants with essential data literacy skills, enabling them to collect, manage, analyse, and effectively communicate data insights using Microsoft Excel, while adhering to best practices in data management.

These Modules are designed for professionals and decision-makers who need to build fundamental data literacy skills, including those in management, policy, or operational roles who work with data but have limited technical experience.

Introduction to R and Basic Data Analysis (Modules 4-6) develops practical programming competencies in R, enabling students to perform fundamental statistical analyses, manipulate datasets, and create basic visualizations using industry-standard tools and workflows.

Suitable for individuals who are comfortable with basic data concepts and seek to develop technical programming skills, including analysts, researchers, and professionals transitioning to more data-intensive roles.

Intermediate Data Analysis with R (Modules 7-9) advances participants' analytical capabilities through mastery of complex statistical modelling, advanced visualization techniques, and professional reporting workflows, preparing them for sophisticated data analysis projects and automated reporting in organizational contexts.

These Modules are ideal for practitioners with basic R programming experience who aim to advance their statistical modelling and automated reporting capabilities, including data analysts, research officers, and professionals who need to implement sophisticated data analysis workflows in their organizations.