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JohnGalt123456789 t1_j1e0qo2 wrote

Reply to comment by AlexHanson007 in Compared to your other family members, how would you rate yourself as a gift giver on a scale of 0-100? [OC] by GradientMetrics

What is your read on the story? Curious, and just wanting a bit more context, if you were willing to provide.

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AlexHanson007 t1_j1e2kr2 wrote

The question was "how do you compare yourself to others". Yet, the graph is not normally distributed but skewed to positive responses.

Unless the survey happened to pick an abnormally large group of the best present givers, it means that the people responding are overrating themselves.

They can't all be amazing!

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PseudoY t1_j1es84d wrote

Ah, but maybe bad gift givers more often refused to respond!

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comicmuse1982 t1_j1fai1y wrote

It's a perfect Lake Wobegone Effect demonstration.

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AlexHanson007 t1_j1fbj6n wrote

Indeed.

Had forgotten the name for that. Thank goodness Google exists.

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TripleATeam t1_j1h5dux wrote

Or... bad gift givers tend to have multiple discrete families?

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basketcase7 t1_j1gewoz wrote

> it means that the people responding are overrating themselves

Only if you assume that gift-giving ability is normally distributed. It doesn't have to be...

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AlexHanson007 t1_j1h6719 wrote

It's a comparison against others, not an independent and absolute rating. Assuming our sample population is not biased and is a fair reflection of society, then it does have to be normally distributed.

What this graph is saying is that, compared to others, most people are better at something. That's not possible. That would be like having a race and saying most people finished in 3rd place (assuming there aren't joint finishes).

As someone else pointed out, this is an example of the Lake Wobegon effect.

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Elendur_Krown t1_j1hfuas wrote

Why would it have to be normally distributed?

In my eyes a non-biased relative comparison could end up with a whole host of distributions. A relative measure only means that you'll translate and perhaps rescale the original distribution.

Do you have a theorem or specific result to refer to?

I should also point out that the Lake Wobegon effect is at its most relevant when the underlying distribution is symmetric. Meaning that the average and the median are equivalent. This does hold for e.g. normal distributions. But if we allow for distributions with long smaller-than-mean tails, it would be possible that a majority are better than the mean.

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