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Nigel Marriott's Blog

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

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

August 11, 2020 By Nigel

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.

[Read more…] about Pay Gaps #17 – How to Spot an Incorrect Median Gender Pay Gap

Filed Under: Diversity Tagged With: Checking for errors, Data Errors, data quality, Gender Pay Fingerprint, Gender Pay Gap, Median, Statistical Thinking

Stats Training Materials – Pay Gap Analytics

May 30, 2020 By Nigel

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

[Read more…] about Stats Training Materials – Pay Gap Analytics

Filed Under: Stats Training Tagged With: Analytics, Data journalism, Gender Pay Gap, Pay Gaps, Presenting data, Statistical Concepts, Statistical Thinking

Stats Training Materials – Basic Statistical Concepts

February 1, 2019 By Nigel

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.

[Read more…] about Stats Training Materials – Basic Statistical Concepts

Filed Under: Stats Training Tagged With: Data journalism, Evidence Hierarchy, Presenting data, Statistical Concepts, Statistical Thinking

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