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May 5, 2016
Ahmed Al-Hindawi
Finn Catling
Steve Harris
Ed Palmer
Danny Wong
Steve Harris
Clinical
Critical Care
R
Under Development

{{ page.domain }} Data Science for {{ page.topic }}

Data Science for Doc's aim is to teach doctors, nurses, and other health care professionals basic concepts, skills, and tools for working more effectively with data. The lessons below were designed for those interested in working with {{page.domain %}} data in {{page.topic %}}.

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We have borrrowed heavily from the excellent Data Carpentry programme in producing this course. However, this is not a data carpentry course. We do not meet their specications (yet), although this is something we are working toward.

Lesson Maintainers: {{page.maintainers | join: ', ' %}}

Lesson status: {{ page.status }}

Before your first lesson ...

Here is a quick checklist but you'll do best to follow the instructions here.

  • bring your own laptop
  • install R
  • install R studio
  • sign up for a Google docs account
  • download and install a speadsheet programme

Full details of the pre-course preparation are available here. If you're interested in why we're recommending in R, then you might enjoy reading this.

After every talk please do fill in our course feedback form.

Finally, please complete the pre-course survey.

Lessons:

We'll cover a number of lessons during the 2 days. The programme is flexible, but an outline is available here.

  1. Preliminaries
  2. R for newbies
  3. Excel Hell
  4. Getting data into R
  5. Data wrangling
  6. Data visualisation
  7. Plotting graphs with ggplot2
  8. Just enough statistics
  9. Data analysis practical

Data

Data files for the lesson are available here:

  • An RCT comparing post-operative pain control after axillary node dissection with local anaesthetic infiltration via the drain versus injection to the skin flaps (Thanks to Muska Khpal)
  • [SPOTlight study data]({{page.dataurl_1 %}}): an observational study of deteriorating ward patients referred to critical care

You are also encourage to bring along your own data. We can't promise to spend time on this, but there are exercises to do along the way, and you might want to try these exercises out on your own work.

Help

Where to get help? Firstly, we'd strongly encourage you to ask the group. To this end, we have set up a slack group - this is an instant messaging service (like whatsapp or similar) but with much better tools for sharing files, and working with code. If you're on the course, you should already have received an invite. Let us know if not.

We'd also recommend the following

Twitter: @datascibc