Key facts

Overview

This online statistics course is designed for busy health and social care professionals who need to understand the basics of health statistics without becoming statisticians. Students can study at the time of day and week that is best for them. Online discussion forums enable students to communicate with each other and with the tutor to analyse and understand real-life scenarios.

The course promotes an online learning community to support and motivate students during the 10-weeks.

"This research looks really useful for my patients. But can I trust the results of the study?"

"I do read the research papers in my field but I tend to skip the statistics."

"I need to get more experience for my exams - but I can't take time off work to attend a statistics course."

If this sounds familiar, then this course is for you.

Description

Who is it for?

The course is aimed at those working in health and social care who have either studied mathematics to AS level or obtained equivalent work based exposure to mathematics.

To take full benefit of the course you should be able to commit 10 hours per week for 10 weeks. Please be aware that participation in the online discussions is a requirement for successful completion of the course.

This module will cover:

This course is divided into 10 units. Each unit covers a different aspect of statistics and statistical modelling.

Individual units are built around practical exercises and realistic case studies that will enable students to apply statistical knowledge in a health context.

Weekly study for each unit is self-paced using online resources. Movement through the units is structured week by week to enable students to complete sections at the same time as the rest of their course group.

Individual activities can involve reading of related text book chapters and articles, working through problems or analysing example datasets. The group activities will mainly involve online discussions of important issues in statistics so that students can put the application of statistics into an everyday context. Discussions occur weekly, but are "asynchronous" due to possible local time differences between the student's locations.

Programme details

Unit Content:

• Handling and describing data, learning to use your calculator
• Probability and random variables
• Exploratory data analysis
• Sampling distributions and statistical inference
• Hypothesis testing
• Analysis of variance
• Linear model and regression
• Statistics applied to cohort studies
• Statistics applied to case control studies
• Statistics applied to randomized controlled trials

Course aims

Benefits

On completion of the course students should:

• be able to understand and manipulate basic mathematical and statistical techniques as preparation for more specialized courses in health care
• understand the statistical issues in the planning and analysis of research
• understand the basic statistical aspects of published research

Assessment methods

The assessment will be in two parts. The first will focus on exercises to assess general understanding of concepts whilst the second will involve exercises that directly relate to Health Research

Oxford University Department for Continuing Education offers credit equivalent to Credit Accumulation and Transfer Scheme (CATS) points for the course. Participants successfully completing the assessment are eligible to earn credit equivalent to 20 M-level CATS points which may be counted towards a postgraduate qualification.

Recommended reading

Scholarships

Details of funding opportunities, including grants, bursaries, loans, scholarships and benefit information are available on our financial assistance page.

Fee options

Programme Fee

For students enrolled on the MSc in Evidence-Based Health Care: £1450.00

Stand-alone short course fee: £1790.00

Apply for this course

Programmes including this module

This module can be studied as part of these programmes:

• MSc in Evidence-Based Health Care
• Postgraduate Diploma in Health Research
• Short courses in health sciences