One shot, once a minute catches a Tit. | Hacker News Reader

One shot, once a minute catches a Tit.

ildekon.blogspot.com

47 pointschanux18 comments

Interesting photo, bad statistical analysis.

The probability of a bird flying in front of the camera exactly as it takes a photo is in no way dependent on how long the camera has been running. Every image capture is an independent event.

There are also many, many webcams in existence, and while there is a low probability of a bird appearing in a photo captured by any specific camera, the probability of some bird appearing in front of some camera at some time would be much higher, and would likely have resulted in a similar amount of attention from bloggers.

Every image is an independent event so the likelihood of a bird appearing in a specific image is unrelated to how long the camera is up. However the likelihood of the bird appearing in any of the images the camera has taken depends on the total number of images. So the analysis is sound.

However I do agree with the second half of you post, the probability of some bird clearly appearing in some shot from some webcam somewhere in the world is very likely near 1.

Good point; I initially interpreted the article's analysis as an attempt to calculate the prior probability of a bird appearing in a specific photo. But then I switched to thinking about the probability of the bird appearing within a sample of photos, which of course depends on the sample size.

Of course, you need to know the prior probabilities in order to calculate the posterior probability distribution, and in this scenario, there doesn't appear to be a reliable way to obtain the prior probabilities, especially considering that there's only a single instance of the event we're looking at in the sample data.

The probability of an event occuring once you know it occured is, surprisingly, "very likely near 1".

Sure, if you're looking at the probability of that specific event occurring.

But if you want to generalize about kinds of events, rather than a single specific one, it's useful to use past events as sample data to estimate probabilities of similar events occurring in the future (provided, of course, that you have defined meaningful categories for entities and events.)

I'll admit I had no idea what I was getting into when I clicked...

I had a very clear idea... I left extremely disappointed.

I was expecting an office webcam and a clothing malfunction, not a titmouse from a webcam I have no clue where it's mounted.

I mean is this out of someones apartment window, is the next screen a bird-splat? Or is this a traffic cam, but if it is why on this puny double-way-road and not a 3-lane highway or on-ramp cam? If this is on a street light, why is it easily 2-stories higher than all the streetlights in the photo.

I'm not so much interested in the bird, but where the heck is this camera mounted?

It isn't one in 2.4 million frames--it's the one that got found out of all N webcams running since the beginning of time.

Glad the title wasn't replaced with '* * *'. Nice tit. Thanks for finding this, hackers.

It's definitely a cool shot, but I'm not sure what the point is in trying to calculate the probability of it happening after the fact.

Good point. If the bird builds a nest in front of the camera, that blows your expected value out of the water.

Unless that bird can hover, I'd hate to think what the next frame looked like.

Probably a smear, since the next frame would have been 60 seconds later.

Somewhat misleading title.

The only reason you calculated the probability is because you observed such an event. Person throws 10 dice and observes 4123532156. "Wow, what are the odds of that?!"

Are there many webcams that do 1280x800 resolution? Or is it more likely a photo?

http://plastik.hu/wp-content/uploads/2007/11/cinke.jpg

Occasionally an ant or fly will crawl across my security webcam and scare the heck out of me for a moment.

I'd say the probability is however many birds have been caught on a webcam in however many webcam pictures have been taken. Roughly.

Destined to become a meme.

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