KIND network update
Week beginning 2024-06-03
Dear colleagues,
This is a quick update to give you a summary of the activities on the KIND network next week. Full details and joining instructions can be found on our Teams channel - please count yourself very welcome there whenever suits. Please also feel entirely free to pass these details to any colleagues who might be interested, and do get in touch with me with any questions or queries.
Brendan
Training
These are drop-in training sessions. No need to book/register - just follow the link on the day. You’ll need to join the KIND Teams channel to follow the chat, and to access sample data files etc.
| Session | Date | Level |
|---|---|---|
| Why bother with…Excel? | 11:00 - 11:30 Thu 06/06/24 | 🥬: a pre-beginner-level session aimed at those with no prior experience |
| Why bother with…R? | 12:30 - 13:00 Mon 03/06/24 | 🥬: a pre-beginner-level session aimed at those with no prior experience |
| R project templates | 14:30 - 16:30 Tue 04/06/24 | 🌶🌶: an intermediate-level session aimed at those with prior experience of the topic |
| Practical Power Pivot | 9:30 - 10:30 Thu 06/06/24 | 🌶🌶: an intermediate-level session aimed at those with prior experience of the topic |
| Scope of the possible with Excel | 13:00 - 14:00 Thu 06/06/24 | 💼: a non-technical session aimed at service leads that gives an overview of the topic |
Events
- 13.00 - 14.00 Tues 2024-06-04. SCODAS meeting. Paul Carroll and Alexander Royle (PHS) - Discovery. The Scottish Community of Data Analysts is a community of practice for those working with data in territorial NHS Boards.
- 13.00 - 14.00 Wed 2024-06-05. The KIND Community meetup theme this week is DAX top tips and best practice . All welcome at our regular Wednesday get-together/webinar/tech demo. Full details and joining links via the community meetup channel
- 15.00 - 16.00 Thurs 2024-06-06. The R reading group session next week will be chapter 2 of Hyndman and Athanasopoulos, 2021. Forecasting: principles and practice, 3rd ed, which deals with time series graphics. Lots of interest in our earlier discussions about forecasting, and this chapter looks like a gentle way into understanding some of the R code (and the theory) needed to do that. We’re also looking for a willing volunteer to lead the session too - you don’t need to do lots of preparation for that, but instead just be familiar with the chapter and have picked out some areas that you think are interesting. Please get in touch if you’re keen.
Book of the week
Ludwig Fleck (Bradley and Trenn, trans.). 1979 (1935). Genesis and Development of a Scientific Fact. ISBN 9780226253252, Worldcat link. If last week’s book was a paean to the use of scientific facts, this week’s book tells a rather more subtle story about how facts. It starts by telling the story of the ‘discovery’ of the Wassermann reaction, and uses that history as the basis for an investigation of the ways in which people came to a) claim that the Wassermann reaction worked because of scientific facts and b) how those facts changes as the Wassermann reaction became used in practice.
From the KIND-ish stance much of the interest lies in the parts of this book that describe how medical research wasn’t the straightforwardly objective story about discovery that we often want to portray. Fleck’s claim, broadly, is that the Wassermann reaction was invented, rather than discovered, and that invention reflected (in part) the social organisation of researchers and others involved in its discovery. Of particular interest to people like us are a series of claims about how facts change as they travel out from the specialist communities that work on them. We’re all familiar with the changes that happen (and need to happen) as we pass the results of our work out to their eventual users: they often get simplified, or put in context, or whatever.
Resource of the week
Our Power BI and Excel training courses are now full, but a great video alternative has been suggested as the resource of the week by Martin Scott (Aberdeenshire Council). This Hands-On Power BI (video) Tutorial covers similar ground to our intro course, and has the advantage of using open (US) data to demonstrate core concepts.
We have a very few spots left on our intro to R and Rmarkdown, Shiny, and intro to evidence-based medicine/critical appraisal courses too, so please feel encouraged to sign-up via TURAS if you’re interested.