Introduction to Statistics in R (online, self-paced)

This course aims to teach you fascinating new statistical skills and a statistical programming language. It is delivered in a self-paced format that you can register for and start at any time.

Flash Sale! Save £125. We’re offering this for just £375 (normally £500). Offer ends Friday 13th June.

Participants will be introduced to the fundamental principles of statistics and to ways of conducting their own analysis, including significance tests and linear regression techniques. The excellent free software Rstudio will be introduced and used for all practical aspects of the course which is a user-friendly interface for R.

The course contains 86 short videos and 32 practical activites. The expected time to completion is 25 hours (the equivalent of a full five-day week in the classroom).

We often run this as a summer / winter school. If you prefer to take this course in a live format, then head over to its dedicated web page.

Click to register (online, self-paced)

Outline

In more detail, this course will cover:

An overview of quantitative research study designs
Types of data
Graphical displays
Summaries of data
Confidence intervals
Hypothesis testing (parametric and non-parametric tests)
p-values
Linear regression analysis

Neither prior knowledge of R (or similar software) nor of statistical analysis is required.

Learning outcomes

At the end of the course, learners should understand the main principles of collecting good data and producing statistics using the R software package. In particular, learners will be able to:

Set out a plan of analysis for a research question accounting for all types of data involved and aspects of their question.
Choose the best way of graphically displaying their data and results.
Choose the significance tests suitable to answer their question.
Make appropriate use of statistical inference methods.
Understand when regression methods are useful.
Choose the most suitable regression model for their analysis.
Evaluate the goodness of fit of the fitted model.
Perform appropriate model diagnostics and predictions.
Perform all the above analyses in the R studio software package.

Fees

Below are the fees for access to the online, self-paced version of this course.

External delegates (non-UCL)	£375 (was £500)
UCL staff, students, alumni	£187.50 (was £250) *
Staff from ICH/GOSH, and doctoral students from UCL †	FREE *

* A valid UCL email address and/or UCL alumni number required. Please note, this category does not include hospital staff unless you have a formal affiliation with the university. To get this discount, please email ich.statscou@ucl.ac.uk to confirm your eligibility and receive a code that can be entered at the checkout.

† If you are a doctoral student from UCL, you can get access to this, and all other self-paced courses developed by CASC by filling in this online form.

What to expect?

This course includes the following materials

Full electronic notes.
Short lecture videos (recorded outside of the classroom with screen recordings and annotation) that follow closely with the notes.
All programming code.
Interactive quizzes for each chapter, and opportunities to collaborate with other learners.

Support: The course includes unlimited support through a forum that will be manned by one of our teaching fellows. We aim to provide responses to all questions on Tuesday and Friday each working week. Note that questions can only relate directly to the course materials and should not be used as a consultancy service for your own projects.

Personalised certificates will be generated on completion (when you pass the multiple choice quizzes).

Feedback (from our other self-paced courses)

The extend feature is so helpful in conjunction with the module. It is exceptionally clear and very well organized so I can keep track of my progress and identify areas where I need to focus further. Thank you CASC :)

Incredible course. I have some experience of statistics but I still found it incredibly useful. Really well laid out with lectures and exercises. Will recommend to everyone.

Excellent teaching valuable resources - comprehensive range of videos, recordings, practicals, practice questions approachable lecturers who made statistics interesting for non-statisticians thoroughly enjoyed the module

Course was put together in an excellent fashion and explanation of the concepts was both clear and thorough. Thank you for clarifying some concepts which I have found difficult to grasp in the past in such a clear way.

The help section was useful, specially when I had questions with the practicals that were not clear on the answers. The fact that this course is self-paced has been very useful and has allowed me to complete it.

Link

Mailing list

Our subscribers are the first to find out about new courses, new dates for existing courses and any other important CASC news.

Join our Mailing List

Bespoke courses

If you are part of a team/organisation that would like statistics training, we can arrange extra dates for our existing courses or prepare something more bespoke.

Enquire about Bespoke Courses

Come to 6 day-courses, get a 7th free!

Once you have attended 6 short-courses, you're ready to claim your 7th day-course for free (please email us to make this arrangement). Our longer introduction course counts as three towards this total.

Contact

Please see our FAQ page before making an enquiry.

Email:
Recommended for general queries/payments:
ich.statscou@ucl.ac.uk

Phone:
For general queries/payments:
+44 (0) 20 7905 2768
To contact a teaching fellow about the contents of a course:
+44 (0) 7730405980

Address:
Centre for Applied Statistics Courses (CASC)
UCL Great Ormond Street Institute of Child Health
30 Guilford Street
London, WC1N 1EH