Nigel Marriott's Blog

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

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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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Pay Gaps #3 – 12 ways to improve public confidence in gender pay gap data

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This is intended to be a briefing note for anyone interested in seeing gender pay gap data being used properly.  Gender pay gap data is now part is the business and political discourse in the UK and is likely to be so for some time.  If the goal of gender pay gap reporting is to remove disparities in pay between men and women, then it is essential that the public has confidence in both the quality of the data being published and the correctness of any interpretations of the results.  With the first round of data reporting out of the way, it is time to learn lessons, identify improvements and see that these are implemented.  Following extensive analysis of the 2017 round of results, I have identified 12 ways to improve the quality of the data being reported and make interpretations of the results more meaningful.
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Pay Gap Case Study #1 – Life on Mars

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The UK is facing the challenge of interpreting the first round of gender pay gap data and I listed some of the challenges in my article “the 7 ways to misuse gender pay gap data“.  In statement 4 of that post, I stated that a lack of understanding of the laws of chance will result in unjustified allegations of gender discrimination against some organisations and so in this article, I want to demonstrate the laws of chance using nothing more than some dice and coins, a process known as simulation.  My simulation model is simple enough for you to repeat by yourselves and at the end, you will have a better idea of the extent to which median gender pay gaps can vary even when organisations do not discriminate in any shape or form.
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