Who is this course for? These days we are all deluged with data and required to make “evidence-based” decisions. This course aims to equip people from all walks of life to be able to be more discerning and critical about data.
Learning Objectives: Attendees will be more confident in assessing and appraising the data and results that are presented to them. They will be more confident to review relevant data and consider: have the right questions been asked; are the conclusions reliable? have we been misled either accidentally or intentionally? are the sources trustworthy; is the analysis thorough and could any bias have crept in?
Course Length and Price: 2 days, £2,900 ex VAT
Pre-requisites: A basic familiarity with Excel may be helpful but not essential, simply because the data in the case studies will be provided as Excel spreadsheets. All the exercises are in groups of three or four people and we will ensure that one person in each group has some Excel experience.
The format is based on group discussion based and exercises. We investigate case studies based on topical questions using public datasets. This is not a “technical” course and does not require any mastery of analytics software.
How to lie with charts and data
Or instead how to avoid being fooled by a dodgy dataset, a vexatious visual or a mendacious map. The presenter will show lots of examples of these for group discussion.
Group Exercise: The top 5%
A recent argument in the UK is whether a person earning £80,000 per year is in the top 5% of earners. We look at some data from HMRC to see if we can settle the argument and also discover some interesting insights into how much people get paid in Britain.
Group Exercise: COVID-19 analysis
This will be a case study using a relevant recent dataset related to the COVID-19 situation
Case Study: UK Election 2019 results
The recent UK elections generate a mass of complex data – for example, how many votes were cast for each party in each of the 650 constituencies in the 2019 election and how do they compare with the 2017 election. Of course, we’ve seen in the media many beautiful and insightful visualisations and analyses. In this exercise, we’ll start with the data and see if we can ask interesting and important questions ignored by the journalists, such as why it helps prospective MPs to be called David.
Below are some images from the case studies on the course.