Program Overview

Introduction to Statistical Analysis and Data Science with R

Overview

The Introduction to Statistical Analysis and Data Science with R is a short course offered by the University of Essex. This 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.

• Title: Introduction to statistical analysis and data science with R
• Module code: MA520
• Module credits: 30 credits
• Module level: Level 4
• Start date: No date available
• Location: Colchester Campus
• Based in: Mathematics Statistics and Actuarial Science

This course covers two main areas: introduction to data science and statistics, and introduction to R for data analysis. No prior knowledge of statistics or R is required, and only basic numeracy skills are needed.

Introduction to Data Science and Statistics

This section introduces the concepts and practice of statistics and data science without requiring advanced mathematical skills or prior knowledge of software.

• By the end of this section, participants will have a comprehensive grasp of statistical and data science methods and their implementation in R.

Introduction to R for Data Analysis

The second part of the course delivers training in R for data analysis, aiming to introduce the power of R for data analysis.

• Participants will take part in face-to-face laboratories on Colchester Campus, where they 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, participants will be able to demonstrate:

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

There are no specific entry requirements for this course, and no background in mathematics or computer science is needed.

Structure

Module Outline

The module will be delivered through a weekly teaching session on Colchester campus, one day per week during term time for 3 hours on a Wednesday afternoon, supported online through contact with the tutor and access to Moodle.

Teaching Schedule

Teaching will take place on Colchester campus every Wednesday from Wednesday 18 January to Wednesday 22nd March, with 3-hour sessions from 4:00 pm to 7:00 pm.

Assessment Strategy

Assessment will consist of:

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

Fees and Funding

The course costs Ł2,310, including all lectures, labs, and assessment costs, as well as access to university facilities. Funding can be applied for through Student Finance Higher Education Short Course Loans.