Continuing Professional Development

Introduction to Statistical Analysis and Data Science with R


The details
Introduction to statistical analysis and data science with R
30 credits
Level 4
No date available
Colchester Campus

We are not currently accepting applications for this course.

This new short course is part of an Office for Students (OfS) funded pilot project to explore flexible courses that expand digital skillsets in data science and analysis.

This course covers the following two areas, which will introduce data and statistical analysis to participants. You do not need a previous exposure to statistics, nor prior knowledge of R. No mathematical skills are required beyond basic numeracy.

Introduction to data science and statistics

You will be introduced to the concepts and practice of statistics and data science, without a requirement to know or use software or have advanced mathematical skills.

By the end of this section, you will have a comprehensive grasp of statistical and data science methods which will have enabled your understanding of their implementation in R.

Introduction to R for data analysis

The second part of this course delivers training in R for data analysis. The aim is to introduce the power of R for data analysis.

Participants will take part in face-to-face laboratories on Colchester Campus, where you will implement a set of R tasks on a data set under the guidance of teaching staff.

Learning outcomes

By the end of the course, you will be able to demonstrate the following:

  1. A sound conceptual knowledge of the basic traditional concepts of Statistics without mathematical development.
  2. A sound conceptual knowledge of modern computer-based data analysis techniques (e.g. Bootstrap methods)
  3. Ability to use R to implement the methodology with a variety of data.

Entry Requirements

We are not currently accepting applications for this course.

Our short courses are designed to be accessible to all. There are no specific entry requirements you need to meet, and you do not need a background in mathematics or computer science to be eligible for this course.


Module Outline

This module will be delivered through a weekly teaching session on Colchester campus, one day per week term time for 3 hours on a Wednesday afternoon.

You will also be supported online through contact with your tutor and access to Moodle.

Teaching schedule

Teaching will take place on Colchester campus every Wednesday from Wednesday 18 January to Wednesday 22nd March. These teaching sessions will be 3 hours long, from 4:00pm to 7:00pm.

Assessment strategy

Assessment will consist of the following:

  • Moodle test based on the book requiring only simple calculations with multiple choice answers, worth 50% of your final mark.
  • A task using R which is similar in nature to the labs, but time limited and managed online for the student to perform remotely, worth 50% of your final mark.

Fees and funding

The course costs £2,310. This includes all lectures, labs and assessment costs, and access to university facilities such as the library, the Silberrad Student Centre and student support services.

Funding for this course can be applied for through Student Finance Higher Education Short Course Loans.

What's next

All applications for this course can be made online.
For further help or information, please contact