Nigel Marriott's Blog

An independent statistician using data to understand our world and to predict the future

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Pay Gaps #25 – Parliament’s debate on Ethnicity Pay Gaps – My thoughts

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The UK Parliament debated Ethnicity Pay Gap Reporting (EPGR) on 20th September 2021 in Westminster Hall.  Seven MPs spoke in the hour long debate and, as debates go, I thought it was actually quite good.  There was cross party consensus on the merits of EPGR but I saw a divide between those who recognise EPGR is complex and requires trade offs and those who think the complexities of EPGR can be solved with government guidance.

 

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6 Nations History #1 – The men’s story so far in 2021

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The 2021 Six Nations (Men’s) ended with Wales winning the title after Scotland beat France in Paris to snuff out France’s attempt to win the title for the first time since 2010.  Wales let a Grand Slam slip after conceding a try in injury time and as an England fan who was there at Wembley in 1999 I know exactly how the Welsh feel!

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Pay Gap Case Study #4 – What is the gender pay gap at Novartis UK?

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Welcome to my next case study where I look at the 2019 pay gap figures of Novartis UK.  They caught my eye when they posted on LinkedIn the following statement.

“… our 2019 gender pay report which highlights that on average, women earn more than men across all of our UK sites and divisions…“

When I looked at the two legal entities that were required to report gender pay gaps, I saw that both reported pay gaps favouring men instead.  Something odd is going here and it’s a perfect case study to show why anyone who analyses pay gaps needs to pay more attention to a Bletchley Park codebreaker from world war 2 who introduced the world to Simpson’s Paradox.

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Stats Training Materials – Pay Gap Analytics

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To close a pay gap you have to do three things:

  1. Measure where you are today.
  2. Specify where you want to be in the future.
  3. Identify the most effective way of getting there.

All 3 steps require the use of statistical thinking and statistical methods.  Of course, other skills and processes are also needed but they cannot succeed on their own without the help of statistics

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Coronavirus #1 – Useful Data and Links

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Updated on 14th May 2020.  New and modified links are italicised.

The Coronavirus Pandemic is a worldwide challenge many of us will have not experienced before.  It is natural to want to seek information on the risks and in our world today, it has never been easier to find data, analyses and opinions.  Unfortunately, a lot of what you will read out there is either unhelpful or actively misleading.  As an independent statistician with 30 years experience of explaining statistics to non-statisticians, my contribution to this crisis will be to try and sort the good from the bad hence this post. [Read more…] about Coronavirus #1 – Useful Data and Links

Coronavirus #3 – How many people have died of COVID19 in the UK?

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The Financial Times (FT) has estimated the true number of COVID19 related deaths in the UK as of 20th April 2020 is 42,000 not 17,000 as published by the Department of Health & Social Care (DHSC).  In this article, I show that the FT headline is incorrect and is the result of either the FT comparing apples with pears due to a misunderstanding over what the various data sets measure or the FT attempting to estimate a number that can never be verified.

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Pay Gaps #13 – How could Ethnicity Pay Gap Reporting be introduced in the UK?

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On 5th February 2020, Baroness Prosser laid a bill in the House of Lords which calls for the introduction of ethnicity pay gap reporting in addition to a number of other initiatives.  Last year I explained why ethnicity pay gap reporting cannot follow the same process as gender pay gap reporting so now is the time to explore how ethnicity pay gap reporting could be carried out.

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Stats Training Materials – Basic Statistical Concepts

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A sound grasp of basic statistical concepts is essential to have any hope of acquiring the mindset of a statistical thinker and to be able to use statistical methods.  My introductory course “The 6 Concepts of Statistical Thinking” lays the foundations in the following.

  1. Probability – the difference between conditional & absolute probability.
  2. Risk – why it is an extension of probability and the importance of alpha (false positive) and beta (false negative) risk.
  3. Expectation – how to summarise a dataset into one number which measures its location.
  4. Variance – how to measure the spread of a dataset.
  5. Distribution – how to describe the shape of a dataset.
  6. Correlation – how to measure the relationship between two variables and understand the two golden rules of correlation.

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