Visualizing statistics

Please note, this event has a very limited capacity, and we are expecting high demand. This training course will take place across two days, with the first session running from 09:30 to 12:45 on Tuesday 24 March , and the second session running from 09:30 to 12:45 on Friday 27 March. 

Please only sign up if you can attend both days. 

Session Overview

Healthcare data analysts need to have some knowledge of the basic statistics syllabus. If they have this knowledge – and if they also know how to incorporate the knowledge into their everyday work – they will produce work of a higher quality. But analysts often either don’t have this knowledge or they have it but they’ve ‘compartmentalized’ it and haven’t thought to apply it to their work. Visualizing Statistics is a course that teaches (or – in some cases - refreshes) analysts’ knowledge of four core elements of the basic stats syllabus. It does this in three ways:

1. THE CONCEPTS

Each session teaches a statistical concept. We use real life case studies to draw attention to problems that need to be solved, and we show how the concept (e.g. standard deviation) can be used to point us towards a solution. Once we can all see the point of the concept, we then discuss what it means and dissect the necessary calculations and keystrokes.

2. THE VISUALIZATIONS

Each session teaches at least one way of visualizing the concept. Statistical concepts can only really be communicated effectively if they are visualized. So a key part of each session is how we design charts that illustrate the statistical concept and help solve the case study problem.

3. THE NARRATIVE EXPLANATIONS

Each session teaches how to present/explain the visualization to a layperson audience. The visualizations can’t stand on their own or speak for themselves; they nearly always have to be explained and presented to groups of healthcare managers and clinicians. We make sure that we know how to do this in user-friendly language.

SUMMARY

Visualizing Statistics adopts a case study approach. It’s hands-on. The exercises (in Microsoft Excel) act as a platform for teaching the concepts. The concepts are (1) distributions and standard deviation (2) time series and quantiles (3) caterpillar plots/funnel plots and confidence intervals (4) scatterplots/bubbleplots and correlation. Participants are encouraged to develop their learning after the course by consulting a ‘suggested reading list’ books, videos and websites.