2019 in the UK began with a dry month but normal weather otherwise.
Pay Gap#1 – 7 ways to misuse gender pay gap data
April 2018 was the deadline for submitting gender pay gap results and we now have the first detailed picture of how pay differs between men and women in the UK. A nifty government website can be used to look up pay gap details for any company employing more than 250 employees and you can also download the results for further analysis. So what will happen next? Will the data be used properly to inform debate about how men and women are paid or will it be misused for personal and political gain?
I believe this data can be of benefit to the debate around gender equality but my fear is that to begin with, it will be misused, misinterpreted and reinforce the saying “lies, damned lies and statistics”. So if you want to misuse gender pay gap data, who better to ask that a professional statistician like me who will show you how you can do this by commenting on 7 plausible statements.
Forecasting#1 – How do you identify a good forecaster?
“I think the people in this country have had enough of experts”
Michael Gove, Sky News, 3rd June 2016
This was one of the most memorable quotes during the EU referendum in 2016 and came in response to a question as to why the forecasts of a whole list of organisations such as the IMF should be ignored. It prompted a flurry of rebuttals and articles supporting or damning him and the debate has not gone away.
Like so many quotes, it has already become distorted. I strongly recommend you listen to the full question and answer because here is his quote in its entirety.
When I read this full quote I realised I am in complete agreement with Michael Gove.
Segmentation #1 – Who has more in common? Leave & Trump voters or Remain & Clinton voters? Analysis of Sentiments
My wife is American and so it should be easy to guess what we were talking about on the morning of 9th November 2016. Donald Trump’s victory in the US Presidential election was a surprise to many people and prompted much discussion on the similarities between Trump voters and the Leave voters in June. However, my wife remarked that people may be looking at this the wrong way round and perhaps the correct question to ask is whether there is greater similarity between Clinton & Remain voters.
Identifying similarities and differences between groups of people is a cornerstone of the field of market research known as customer segmentation. It is one of my favourite areas of statistics and can be used regardless of whether the data comes from a survey or from customer records. When my wife posed her question I immediately thought of 2 ways I could answer this using segmentation methods.
- Look at how people feel (their sentiments) which is what this post is about.
- Look at how people voted (their behaviour) which I will cover in another post “Who has more in common? Leave & Trump voters or Remain & Clinton voters? Analysis of voting behaviour”
EU Referendum 2016 #1 – How and why did Leave win and what does it mean for UK politics? (a 4-part special)
I am delighted to announce my 4-part series describing my analysis of the EU referendum results is now complete and available on Youtube. The full list of the clips are:
Part 1 – Where and How did Leave win?
Part 3 – What does the leave vote mean for the next general election?
Part 4 – How will Brexit play out in the Richmond & Sleaford by-elections
I have analysed the results of the EU referendum in some depth and I hope you find my insights informative. Some specific highlights are:
