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by dkobran·4y ago·view on hn ↗
> This article compares the wages not of all CEOs, but of 300 of the best paid ones.

That is not true. The report analyzes “publicly held companies with the lowest median worker pay.” They describe the sample probably a dozen or so times in the report.

> tiny fraction of one side to millions

You are making this out to be a random sample of irrelevant companies. These are publicly traded companies of which there are a few thousand in total. The list includes companies such as Amazon, Target, Best Buy, Lowe’s, Estee Lauder, etc.

Who’s trying to elicit outrage, you or them?

1 comments
Me: "This article compares the wages not of all CEOs, but of 300 of the best paid ones."

You: "That is not true."

The article: "Report on 300 top US companies...."

Tell me again this is not 300 of the best paid CEOs? After all, the fact is CEO average pay is only 212k. BLS is a much better source than the Guardian for salary data, after all.

>You are making this out to be a random sample of irrelevant companies.

It is most certainly not a random sample of companies, otherwise the result would mimic the actual data from BLS. This is specially selected data to get this result.

It is a cherry picked sample of the very top end of the CEO salaries (300 of them out of over 200,000 of them that exist) compared to workers, but not all workers, only those that are among the lowest paid, again, to reach a shocking headline that creates outrage.

Here's [1] the actual report. Note in the report they compare part time worker wages to fulltime CEOs - not an hourly rate or something a tiny bit more defensible - for example, they compare an annual wage of $224 (yes, you read that correct) for a part time worker at NuSkin to the CEO wage of $4m. They repeat this type of nonsense throughout the report. The dishonesty in the report to me is astounding - and it explains how they get the numbers to drive their headlines.

Comparing a tiny fraction of top values from one dataset to all of another dataset is not exactly a valid statistical technique. Doing everything you can at each step to widen the result to get what you want is beyond simple stats misunderstanding - it's nutjob agenda driven lying.

If someone did this to claim global warming was not real, or any of a zillion other false claims, people would (and should) cry foul.

If I did this, picking the top 300 employee wages in the country (all well into the millions) and compared to all CEOs (avg pay 200k), obtaining the claim that workers make many multiples of CEO wages, you'd rightfully cry foul.

So why the pitchforks and intellectual dishonesty when the data is manipulated this way? Because it gets a result you want to see?

[1] https://ips-dc.org/wp-content/uploads/2022/06/report-executi...