I just stumbled across this set of facts:

"Every year more than 1.17 million people die in road crashes around the world. The majority of these deaths, about 70 percent occur in developing countries. Sixty-five percent of deaths involve pedestrians and 35 percent of pedestrian deaths are children"

http://www.worldbank.org/html/fpd/transport/roads/safety.htm

I had no idea that so many of the road crash deaths were of people not in the cars. It makes our discussion about how safe it is to be inside an SUV in a crash kind of irrelevant.

Very intersting, I would have never guessed either. 35% Children? Thats kind of depressing.

Well, 35% of 65%, so 22.75% of total deaths. But still....

Also, as an example of how statistics can be misleading, it says ``65% involve pedestrians'' (emphasis mine). What does that mean? Maybe it includes driver and passenger deaths that occurred while trying to avoid pedestrians and the pedestrian didn't die, or, potentially, even get injured.

Also, what is the percentage of children in total population? If you have a wealthy population where most people die when they get quite old, and not too much before, and you assume that a child is someone less than 18, and average lifespan is 75, then the percentage of children in the population is 24%. But in developing countries, the percentage of children is much higher, as people don't live to be as old, and there's a marked tendency for people to die throughout their lives, so, with a large portion (70%) of the sample being from developing countries, 35% children might match population fairly well.

The most interesting statistic might be the fact that 70% of them are in developing countries. That probably just points to the fact that there's a much greater auto-to-pedestrian ratio there than in developed countries, and there's probably something in the even worse training of drivers there, as well as worse infrastructure (roads, traffic signals, etc.). But then again, what's the percentage of the world's population that live in developing countries? Might it be around 70%? It wouldn't surprise me. (Are rural China and India considered ``developing''?)

Once you look at it, it doesn't seem too outstanding, does it?

Edit: Oops, misread something.

>>But in developing countries, ... there's a marked tendency for people to die throughout their lives"

That has just made my day

Uhhh. Oops.

I picked the wrong day to stop sniffing glue.

I'm sure you figured it out, but I meant to say that the standard deviation of people's lifetimes is much greater in developing countries than in established countries.

I'm glad you didn't say that. It would have caused confusion amongst many of us and painful flashbacks to wasted math classes in our teens to the rest of us.

there's a marked tendency for people to die throughout their lives

I feel like that every Monday morning

Okay....

The ages at which people commonly die in developing countries is in a much larger range than the ages when people in established countries die.

or

While people in established countries usually live about the same amount of time, those in developing countries live widely differing amounts of time.

or

The expected lifespan of a person in an established country is much less variable than the expected lifespan of a person in a developing country.

or

It's more common for people in developing countries to drop dead at any time than it is for people in established countries.

Do you like any of those better?

In reply to:

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but I meant to say that the standard deviation of people's lifetimes is much greater in developing countries than in established countries.

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Hey, Bitt, I can tell, its not your day to day.

I know what you mean with the above sentence, but what you actually said is pretty much like the earlier comment about people having a tendancy to die throughout their lives.

I don't need to point out, but I will anyway, for the benefit of our other readers [you know who you are :-)) ] that the word "standard" in standard deviation is there, as this statistical concept lets you can compare variability of actual numbers (like age of death) across different populations [e.g. developed versus undeveloped world].

The actual gauge of the variability in a statistical measure is the variance - (of which the standard deviation is the square root and so relates to the variance, but it is subtly a different measurement).

What you really meant to say is the average (or mean) age of death will probably be much be lower in a developing country and the "variance" around this average figure will also be quite large due to the existence lots of early deaths in childhood and also due to the presence of a few very old people.

As compared to the west say where much fewer numbers of children die and the aged tend to live longer lives as well.

In fact, if you look at the "average life expectancy" statistic that gets bandied around from time to time, you will note how the Average life expectancy at birth in the 1800's in the UK was about 43 and now its 74 or something and rising.
[and its also quoted as only 35 or so for cavemen in some books I've read].

That doesn't mean that most people died at 43 in the UK in 1800's - although thats the meaning you would take at first glance.

All it says that if you average the age of death across everyone born in any one year in the 1800's that average value was 43 years old, of course many people live longer than that, and many,many more children died before they reached say, 5 years old and these figures tend to increase the variability of the age of death figure.

What that statistic also doesn't show (unless you dig a lot further) is that most of the improvement in this average life expectancy figure since the 1800's was gained through reducing dramatically the incidence of death in early childhood [so-called infant mortality].

And this has the dramatic effect of pushing the average age at death right up to 74 or whatever it is now.

Sure the fact that we live longer helps too, but thats mainly due to the fact that adding values above the average figure to a set of values, pushes the mean/average value higher.

i.e. not dying before you exceed the current average "age at death" figure helps push the average age of death figure higher.

Serves me right for sleeping through my statistics classes.