Nigel Marriott's Blog

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

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Pay Gaps #19 – Employers should report their Ethnicity Pay Fingerprints

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The UK government has promised to give their views and proposals for introducing Ethnicity Pay Gap (EPG) reporting by the end of 2020.  A year ago, I pointed out statistical, data & ethical issues with EPG and listed 5 possible ways EPG could be introduced but I have not yet focused on what employers should be reporting.  I have now concluded that Ethnicity Pay Fingerprints are vastly superior to Ethnicity Pay Gaps and my new recommendation is that all employers with 500 or more employees should be required to report their Ethnicity Pay Fingerprint (EPF) instead of their Ethnicity Pay Gap.  If EPF is widely adopted and found to be beneficial then I would recommend that reporting of other protected characteristics such as gender & disability should be reported using Pay Fingerprints instead of Pay Gaps.

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Pay Gaps #18 – 10 quick and easy ways to close your gender pay gap!

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You’ve just calculated your latest gender pay gap.  With a sigh, you note that it is still large and at current rate of progress, it will take you 30 years to close it.  Surely there must be a quicker and easier way to eliminate your pay gap?  The good news is that if you use the 10 tools of Creative Pay Gapping, you can eliminate your pay gap tomorrow!

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Data Driven Decision Making #1 – New Statistical Guidance for Land Contamination Surveys

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On 30th September 2020, CL:AIRE (the industry body for the land contamination & remediation sector) published new professional guidance for “Comparing Soil Contamination Data with a Critical Concentration“.  The 46-page document advises how to use statistics when assessing land contamination and deciding whether it is safe for development.  I was the lead author of the guidance and I spent 4 years working with CL:AIRE’s steering committee on what the guidance should cover.  The 4 years were bookended by statement & editorial published by the ASA (American Statistical Association) on the use & misuse of P-Values in 2016 & 2019 respectively and in writing this guidance I felt was I an ambassador for turning those into something that could used by non-statisticians to make real life decisions that have an impact on us all.

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COVID19 Cases #1 – Latest Data and Trends for England

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Last updated on 27th September 2020 but downloadable spreadsheet in section 3a was updated on 19th October 2020.  I will update the post when I get the time!

The latest data for COVID19 (Coronavirus) cases in England as of Saturday 26th September 2020 shows the number of people testing positive for COVID19 is up 60% from a week ago but this masks extreme regional disparities that make the national trend meaningless.  The North is in the grip of a second wave unlike the South which is not.  Unless recent trends in the North abate, the scenario of 50k positive tests per day by the end of October recently postulated by the Chief Scientific Officer remains feasible.

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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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Pay Gaps #17 – How to Spot an Incorrect Median Gender Pay Gap

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I have a spotted an incorrect median gender pay gap published by a well known name in a certain industry.  They shall remain nameless for now since I am trying to get them to accept their error and publish a new gender pay gap report on their website.  I know they have made an error because their published data violates the laws of mathematics as I will explain in this blog.  All it takes to spot such an error is a simple calculation you can do in your head and an understanding what the median measures.

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