Why is everyone passing me on the road (they aren't)?

[Midpack]

This is a post about the related math, so if "numbers is hard" to you, you may not be interested. But since there are a lot of engineers and other technical types here, thought it might appeal to some.

It's a short article explaining one of the reasons why an individual can "see" things very differently than things really are. Why does everyone at the gym seem to be in better shape than me? Why does everyone seem to have more friends than me? And the like...

Just for the fun of it Friends You Can Count On - NYTimes.com

[easysurfer]

Very interesting article.

I always thought the reason folks pass me by while walking is a sign I'm getting older as I remember years ago, I was one of the folks thinking everyone is moving too slow, now it's the other way around .

[Richard4444]

Now I remember why I left engineering in my 2nd year of College.

[Meadbh]

Now I remember why I enjoyed math! Dang it, shoulda been an engineer.....

[Ed_The_Gypsy]

I don't think I live on the same planet as the NYT.

[audreyh1]

Quote:

Originally Posted by Ed_The_Gypsy I don't think I live on the same planet as the NYT.

+1

I don't tweet, friend, like or poke, so NYT definitely describes different universe than mine. And I never worried about how many friends I had in real life either or whether anything was more X than average.

And everyone passes me on the road because I don't drive that fast.

OK, I do confess to actually deigning to like something on occasion, but that's only because the nature parks around here post wildlife sightings/photos on their Facebook pages. We had to come up with a quasi-anonymous persona to participate.

[MBAustin]

Very interesting, thanks Midpack for posting.

I especially liked the college class size example - that really makes sense.

[ls99]

Geez, is this what passes for Phd thesis nowadays?

[freebird5825]

Quote:

Originally Posted by ls99 Geez, is this what passes for Phd thesis nowadays?

At Cornell, no less.

Graduating from Cornell University has historically not been for the faint of heart academically.

[ERD50]

Quote:

Originally Posted by Ed_The_Gypsy I don't think I live on the same planet as the NYT.

Quote:

Originally Posted by ls99 Geez, is this what passes for Phd thesis nowadays?

It makes no sense. I gave up at this point:

Quote:

For example, imagine going to the gym. When you look around, does it seem that just about everybody there is in better shape than you are? Well, you’re probably right. But that’s inevitable and nothing to feel ashamed of. If you’re an average gym member, that’s exactly what you should expect to see, because the people sweating and grunting around you are not average. They’re the types who spend time at the gym, which is why you’re seeing them there in the first place. The couch potatoes are snoozing at home where you can’t count them. In other words, your sample of the gym’s membership is not representative. It’s biased toward gym rats.

If you go to the gym, then you are one of the 'gym go-ers'. So you can be compared to the average of the 'gym go-ers'. But they compare you to the 'gym go-ers' on one hand, and then the total universe of people, including the couch potatoes on the other.

Assuming normal distribution at the gym, then average is average. And that average is likely higher than the average of the entire population - no surprise there. It does not hold that the 'average' gym member would be below the average of the gym members.

OK, so I did read further - the 'average class size' isn't an issue at all - those are just different answers to different questions - that is surprising? I didn't follow the 'friends' thing, as I don't do much social media, but it didn't make any sense to me. And based on the two other examples, I won't invest any time on that one.

-ERD50

[JoeWras]

I scanned the article.

My take away was the author was partly discovering the difference between average and median.

One reason so many monetary statistics are taken as median is because of the problem of average skew.