Private pilot dropout hours - US
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Private pilot dropout hours - US
I'm trying to make sense of chart 1.2 in Paul Craig's book 'The Killing Zone' which seems to show that pilots are most at risk of a fatal accident between 100 and 350 hours.
If I understand correctly, the numbers on the chart are simply the raw numbers of fatal accidents, binned by the number of pilot hours at the time of the accident. This approach will only be valid, if almost all the 200 hour pilots (who don't die) carry on flying until they have at least 1000 hours (the maximum on the chart).
For example, if there are more than 4 times the number of 300 hour private pilots compared with 1000 hour pilots, then we should actually conclude that 1000 hour pilots are more likely to have a fatal accident after making the necessary correction. Now this seems unlikely to me, but I do wonder whether the 'killing zone' is less significant than Paul Craig appears to argue.
Is there anywhere I can find statistics about the average PPL's flying experience in the US, or whether the concept of the 'killing zone' been corroborated by other investigators? The book mentions a 1974 NTSB study but doesn't reference it and I can't find it online.
If I understand correctly, the numbers on the chart are simply the raw numbers of fatal accidents, binned by the number of pilot hours at the time of the accident. This approach will only be valid, if almost all the 200 hour pilots (who don't die) carry on flying until they have at least 1000 hours (the maximum on the chart).
For example, if there are more than 4 times the number of 300 hour private pilots compared with 1000 hour pilots, then we should actually conclude that 1000 hour pilots are more likely to have a fatal accident after making the necessary correction. Now this seems unlikely to me, but I do wonder whether the 'killing zone' is less significant than Paul Craig appears to argue.
Is there anywhere I can find statistics about the average PPL's flying experience in the US, or whether the concept of the 'killing zone' been corroborated by other investigators? The book mentions a 1974 NTSB study but doesn't reference it and I can't find it online.
I think you're doomed to find very little information.
The USA seems to regard central collation of statistics as some massive infringement of personal liberties, so hours on either pilots or airframes are not really available.
You might get something from either US-AOPA or the US Air Taxi Survey, but I'd not hold out much hope.
For the UK, there are statistics sourced from the CAA that are regularly published in Flight Training News. I doubt many other countries are so helpful to the safety researcher.
G
The USA seems to regard central collation of statistics as some massive infringement of personal liberties, so hours on either pilots or airframes are not really available.
You might get something from either US-AOPA or the US Air Taxi Survey, but I'd not hold out much hope.
For the UK, there are statistics sourced from the CAA that are regularly published in Flight Training News. I doubt many other countries are so helpful to the safety researcher.
G
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abgd,
You've alluded to one of the key problems with "The Killing Zone", which is that the statistics have been mis-represented in terms of conclusions.
The book is an incredibly valuable resource for a new PPL, in that the majority of the advice in it, and the case studies are filled with valuable tips and learnings, but the conclusion that there is a "killing zone" in terms of hours flown has been based on a lack of understanding of the statistics being analysed, as well as of the subject of statistical analysis.
As well as your own observation about pilots who don't die needing to fly for X hours longer, there are also countless other aspects which haven't been normalised properly, but one of the biggest issues is that there is no way to draw those conclusions from the data unless those who died in "the killing zone" were allowed to carry on flying after they were dead to see whether they killed themselves again every 100 hours or so.. making them (for possibly some other reason) predisposed to dieing every 100 hours or so - for example. This would no longer show a "killing zone" at all.
The fact that the people who die in the "killing zone" are then removed from the future statistics means that you are unable to draw those conclusions on them.
Ignore the stats, they're fairly meaningless. But take GREAT care to look at each subject (which really do seem to be the key reasons for pilots dieing) and use your best endeavours to avoid the pitfalls / mitigate against the biggest risks. In that, alone, the book is a really valuable resource.
You've alluded to one of the key problems with "The Killing Zone", which is that the statistics have been mis-represented in terms of conclusions.
The book is an incredibly valuable resource for a new PPL, in that the majority of the advice in it, and the case studies are filled with valuable tips and learnings, but the conclusion that there is a "killing zone" in terms of hours flown has been based on a lack of understanding of the statistics being analysed, as well as of the subject of statistical analysis.
As well as your own observation about pilots who don't die needing to fly for X hours longer, there are also countless other aspects which haven't been normalised properly, but one of the biggest issues is that there is no way to draw those conclusions from the data unless those who died in "the killing zone" were allowed to carry on flying after they were dead to see whether they killed themselves again every 100 hours or so.. making them (for possibly some other reason) predisposed to dieing every 100 hours or so - for example. This would no longer show a "killing zone" at all.
The fact that the people who die in the "killing zone" are then removed from the future statistics means that you are unable to draw those conclusions on them.
Ignore the stats, they're fairly meaningless. But take GREAT care to look at each subject (which really do seem to be the key reasons for pilots dieing) and use your best endeavours to avoid the pitfalls / mitigate against the biggest risks. In that, alone, the book is a really valuable resource.
Thread Starter
unless those who died in "the killing zone" were allowed to carry on flying after they were dead to see whether they killed themselves again every 100 hours or so.. making them (for possibly some other reason) predisposed to dieing every 100 hours or so - for example. This would no longer show a "killing zone" at all.
I found quite a few bits in the medical chapter that just struck me as not being so much 'wrong' as... confused ("Alcohol is absorbed into the blood's haemoglobin faster than oxygen") so I confess I was rather losing faith in the book. For the price, and from an academic publisher, I was expecting something rather more rigorous.
There are bits that seem well written so I shall do as you suggest and plow through it before coming to any further judgement.
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You mean, are there a few people who are just so likely to kill themselves, that they almost inevitably do so within a few hundred hours of getting their licences?
It's like saying that virtually nobody succeeds in stealing the crown jewels before they reach 120 years of age
If you read American pilot forums (as I have been since Usenet used to be the main "forum" for aviation years ago) you find that the USA has the same problem as the UK in that nearly everybody chucks it in very quickly, and only the most determined hang on, for a bit longer, and then only the most obscessive types hang on after that
Over there they like to moan that the average age at Oshkosh gets 1 year higher every year and is now around 60
That said, Americans tend to hang in there a good bit longer than the Brits, probably simply because GA has a lot of utility value out there (H24 airports everywhere, good "going places" pilot training, etc, etc).
There is no "killing zone" once you adjust for hours flown etc. and that data doesn't publicly exist - in the USA or in the UK.
The UK CAA does have quite a lot of data which it for some reason doesn't publish (e.g. how long pilots retain their medical after the initial issue) - I believe because it would show GA in poor light but like the FAA they will have this kind of data so one could estimate the dropout rate fairly well.
What there is no decent data on however is annual flying hours. Informal surveys suggest that the UK average is somewhere in the 10-20 hours/year, but there will be a big standard deviation on that.
Last edited by peterh337; 30th Dec 2011 at 18:53.
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That is virtually guaranteed to be true, since only a tiny % of pilots get past a few hundred hours 
There is no "killing zone" once you adjust for hours flown etc. and that data doesn't publicly exist - in the USA or in the UK.
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Are the stats really so misleading? Since one can only have one fatal accident, isn't it relevant that most of those relate to low hours pilots? The dropout rate along the way to high hours doesn't change that fact does it? Whether or not I go on to acquire higher hours doesn't affect the chances of my having a accident tomorrow. And, if I do get those higher hours, my chances of a fatal accident on the same day 10 Years hence are lower I think. But, I've not studied stats so happy for someone to tell me why my analysis is flawed.
Thread Starter
I don't know how misleading the statistics are... It's possible that they're a good approximation, but from what Peter says this seems unlikely.
Try this imaginary scenario for size... Due to an administrative error at EASA it becomes impossible to legally train any new private pilots as of 2012... By April 2020 almost all the pilots still flying will have over 200 hours, though a few stragglers may have just 93. If you plotted a graph of fatal accidents by pilot airtime, you would now have very low figures for low airtime pilots, because there simply wouldn't be that many around. Your graph would seem to imply that higher airtime pilots are more likely to have accidents, but this would be wrong too.
I follow your reasoning that a more experienced pilot will be a safer pilot. On the other hand - it may not be true. More experienced pilots may be doing more challenging flying, or may be getting sloppy - counteracting the benefits of their experience. But what I would say is that if you can't put together decent evidence to support an idea, it's better not to give any evidence at all.
Try this imaginary scenario for size... Due to an administrative error at EASA it becomes impossible to legally train any new private pilots as of 2012... By April 2020 almost all the pilots still flying will have over 200 hours, though a few stragglers may have just 93. If you plotted a graph of fatal accidents by pilot airtime, you would now have very low figures for low airtime pilots, because there simply wouldn't be that many around. Your graph would seem to imply that higher airtime pilots are more likely to have accidents, but this would be wrong too.
I follow your reasoning that a more experienced pilot will be a safer pilot. On the other hand - it may not be true. More experienced pilots may be doing more challenging flying, or may be getting sloppy - counteracting the benefits of their experience. But what I would say is that if you can't put together decent evidence to support an idea, it's better not to give any evidence at all.
Statistics are only as good as the underlying data and require a very clear understanding of what the question was.
Personally I think the advancing the idea that any one persons likelihood of having an accident will vary by the amount of flight time they have is pointless.
What is worth discussing IMO is the fact that the risks of any particular flight should be well understood and ameliorated as much as practicable.
For example the accident rate as expressed by accidents per 100,000 hrs is much worse for PPL's flying VFR at night as compared to those flying during the day. As well a much higher percentage of night accidents result in fatalities as opposed to daytime accidents. I see a lot of PPL's that treat day and night flights pretty much the same. By not acknowledging and dealing with the extra risks they greatly increasing their exposure to an accident and that exposure is pretty much independent of total flight time.
Personally I think the advancing the idea that any one persons likelihood of having an accident will vary by the amount of flight time they have is pointless.
What is worth discussing IMO is the fact that the risks of any particular flight should be well understood and ameliorated as much as practicable.
For example the accident rate as expressed by accidents per 100,000 hrs is much worse for PPL's flying VFR at night as compared to those flying during the day. As well a much higher percentage of night accidents result in fatalities as opposed to daytime accidents. I see a lot of PPL's that treat day and night flights pretty much the same. By not acknowledging and dealing with the extra risks they greatly increasing their exposure to an accident and that exposure is pretty much independent of total flight time.
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To draw conclusions from accident stats one needs to have an idea of the population size, and also of the kind of flying they do.
For example let's say you have two groups of pilots, 100 each, flying same hardware and having had the same training and total hours. Both are instrument rated.
If you get one group to do day VFR only, and the other group to do IFR night flights, there will be a big difference in the accident numbers.
The biggest piece of stats which is missing from GA is what kind of flying different people do. To get that, somebody would have to do serious work and understandably nobody seems keen to do that
The regulators (CAA or FAA) could do postal surveys but few pilots are going to give frank answers in those to questions like how much ice they picked up
For example let's say you have two groups of pilots, 100 each, flying same hardware and having had the same training and total hours. Both are instrument rated.
If you get one group to do day VFR only, and the other group to do IFR night flights, there will be a big difference in the accident numbers.
The biggest piece of stats which is missing from GA is what kind of flying different people do. To get that, somebody would have to do serious work and understandably nobody seems keen to do that
The regulators (CAA or FAA) could do postal surveys but few pilots are going to give frank answers in those to questions like how much ice they picked up
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Peter, even that would be misleading if it were used to jump to conclusions.
BPF is on the money. Stats are just stats. The conclusions that have been drawn from them are the problem.
CharlieDeltaUK. A good illustration of how the *meaning* of the stats are changed by the people who died :
Imagine you're on a gameshow, and there are three boxes. One of them contains a million pounds, the other two contain nothing.
You are asked to select a box, and you select box number 2 (for instance).
The host then explains he'll remove one of the other two boxes, but in doing so he will not remove the million pound box. (eg. If both unselected boxes are empty, he'll just take one at random, but if one of the two boxes is the million pound box, he will remove the empty one).
There are now two boxes. One of them has the million pounds in it. You are given one final chance to stick with the box you had already selected, or to swap.
Statistically speaking - what should you do? Stick or swap?
Most people would say "it makes no difference, it's 50/50" but it isn't.
(Spoiler : Answer / explanation if you're thinking about it : The million pounds is TWICE as likely to be in the OTHER box. So you will double your chances by swapping. The first selection you made had a 2 in 3 chance of being empty. and a 1 in 3 chance of being a million pounds)
BPF is on the money. Stats are just stats. The conclusions that have been drawn from them are the problem.
CharlieDeltaUK. A good illustration of how the *meaning* of the stats are changed by the people who died :
Imagine you're on a gameshow, and there are three boxes. One of them contains a million pounds, the other two contain nothing.
You are asked to select a box, and you select box number 2 (for instance).
The host then explains he'll remove one of the other two boxes, but in doing so he will not remove the million pound box. (eg. If both unselected boxes are empty, he'll just take one at random, but if one of the two boxes is the million pound box, he will remove the empty one).
There are now two boxes. One of them has the million pounds in it. You are given one final chance to stick with the box you had already selected, or to swap.
Statistically speaking - what should you do? Stick or swap?
Most people would say "it makes no difference, it's 50/50" but it isn't.
(Spoiler : Answer / explanation if you're thinking about it : The million pounds is TWICE as likely to be in the OTHER box. So you will double your chances by swapping. The first selection you made had a 2 in 3 chance of being empty. and a 1 in 3 chance of being a million pounds)
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Thankfully I don't think enough of us are going to die flying, that it becomes worth worrying about the Monty Hall problem! I don't even believe it's applicable to the question - the difference is that there is a rule that in one of the boxes there will be a prize. If you take 100 pilots, there is no rule that a given number of them will die - just a statistical probability.
But I think it would be wrong to dismiss the 'killing zone' as meaningless, if it were valid. For example, it would give you some guidance as to how many hours you should have before you can get a CPL and take paying passengers.
I think it alarmed me when I heard about it, because I thought 'My... - I have to fly 300 hours before I will be able to think of taking friends and family for a joy ride?!'
But I think it would be wrong to dismiss the 'killing zone' as meaningless, if it were valid. For example, it would give you some guidance as to how many hours you should have before you can get a CPL and take paying passengers.
I think it alarmed me when I heard about it, because I thought 'My... - I have to fly 300 hours before I will be able to think of taking friends and family for a joy ride?!'
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Thread drift.
Why is the prize twice as likely to be in the other box? After an empty box has been removed you are left with two boxes and the prize is in one of them. If there was an equal (1/3) probability of the prize being in each of the 3 original boxes and then an empty boxes is removed, the two remaining boxes had an equal (to each other) probability of the prize having been placed in either of them. Having completely removed one box from the situation and leaving two, with equal probabilty, then surely the probability can only be 50% and there is no benifit to changing box.
I think your logic is flawed. At the start you think that there is a 1/3 chance of choosing the winning box and therefore a 2/3 chance the winning box not being the one you chose. When one box is removed leaving only one other box, you are thinking that the 2/3 chance of the prize being in a box you did not choose, versus 1/3 chance of it being in your choice remains valid. This is not the case.
Think of it this way. At the beginning one box 'contains the prize'. Another box is 'empty and will be left'. The last is 'empty and will be removed'. You are attaching a 1/3 probability to each box, but if you think about it, you cannot possibly select 'empty and will be removed'. So the real probabilities are:
'contains the prize' 50%
'empty and will be left' 50%
'empty and will be removed' 0%
Why is the prize twice as likely to be in the other box? After an empty box has been removed you are left with two boxes and the prize is in one of them. If there was an equal (1/3) probability of the prize being in each of the 3 original boxes and then an empty boxes is removed, the two remaining boxes had an equal (to each other) probability of the prize having been placed in either of them. Having completely removed one box from the situation and leaving two, with equal probabilty, then surely the probability can only be 50% and there is no benifit to changing box.
I think your logic is flawed. At the start you think that there is a 1/3 chance of choosing the winning box and therefore a 2/3 chance the winning box not being the one you chose. When one box is removed leaving only one other box, you are thinking that the 2/3 chance of the prize being in a box you did not choose, versus 1/3 chance of it being in your choice remains valid. This is not the case.
Think of it this way. At the beginning one box 'contains the prize'. Another box is 'empty and will be left'. The last is 'empty and will be removed'. You are attaching a 1/3 probability to each box, but if you think about it, you cannot possibly select 'empty and will be removed'. So the real probabilities are:
'contains the prize' 50%
'empty and will be left' 50%
'empty and will be removed' 0%
Last edited by Torque Tonight; 31st Dec 2011 at 09:47.
Thread Starter
The Monty Hall problem is all about information. When the gameshow host gives you information that the prize is not in one of the boxes, you have to adjust your estimates of the probabilities of it being in the other boxes. If you type 'monty hall' into Wikipedia you'll probably find a better explanation.
The only way I've ever found to understand the problem intuitively, is to imagine that there are a lot more boxes.
For example, imagine that there are 100 boxes rather than 3. Your first guess is that the prize is in box 100. If the host now opens all the boxes except box 100 and box 57, the chance is now 99% that the prize is in box 57, and only 1% that it is in box 100.
Or even imagine that you never picked a box to start off with - the host opens all the boxes except no. 57 - the chance of the prize being in that box is now 100%
I remember once discussing it with a professional statistician who agreed that the result was correct, but who at the time (either the problem had just been formulated, or it had just got popular) admitted that she just didn't get it.
The only way I've ever found to understand the problem intuitively, is to imagine that there are a lot more boxes.
For example, imagine that there are 100 boxes rather than 3. Your first guess is that the prize is in box 100. If the host now opens all the boxes except box 100 and box 57, the chance is now 99% that the prize is in box 57, and only 1% that it is in box 100.
Or even imagine that you never picked a box to start off with - the host opens all the boxes except no. 57 - the chance of the prize being in that box is now 100%
I remember once discussing it with a professional statistician who agreed that the result was correct, but who at the time (either the problem had just been formulated, or it had just got popular) admitted that she just didn't get it.
Last edited by abgd; 31st Dec 2011 at 11:15.
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abgd,
With respect, you're missing the point, which is :
Statistics are altered by previous events : eg. You selected a box, which affects which box the hosts takes, which affects your odds of then selecting a winner. AND .. by dieing at 100 hours, you affect whether or not you can die at 200 hours, or 1000 hours.
There are so many ways to recreate the "killing zone" stats without it proving that the "number of hours flown so far" is the factor which causes it.
The simplest (but really there are unlimited ways) is if you imagined the following to be true :
1) 90% of pilots only fly for up to 150 hours before giving it up.
2) Most pilots are in training / have a safety pilot with them for the majority of their first 100 hours.
This alone would create a "killing zone" even if all pilots had EXACTLY the same chance of dieing per hour flown.
Then let's say that there are just some types of people who are more likely to die. Those people remove themselves from the statistics pool once they die.
I'm not saying "THERE IS NO KILLING ZONE".. I'm saying "There is no evidence in that book which even begins to suggest there is one".
My gut instinct is that the longer you fly, the safer you are. It seems fairly intuitive to believe that, and your suggestion "i need to fly 300 hours before I'm safe" might not be wrong. But the thing you'd be very brave to assume is "I'm safe to take family and friends when I'm at 75 hours, but then once I get to about 120 hours, I need to stop flying them for a while as I'm less safe".
With respect, you're missing the point, which is :
Statistics are altered by previous events : eg. You selected a box, which affects which box the hosts takes, which affects your odds of then selecting a winner. AND .. by dieing at 100 hours, you affect whether or not you can die at 200 hours, or 1000 hours.
There are so many ways to recreate the "killing zone" stats without it proving that the "number of hours flown so far" is the factor which causes it.
The simplest (but really there are unlimited ways) is if you imagined the following to be true :
1) 90% of pilots only fly for up to 150 hours before giving it up.
2) Most pilots are in training / have a safety pilot with them for the majority of their first 100 hours.
This alone would create a "killing zone" even if all pilots had EXACTLY the same chance of dieing per hour flown.
Then let's say that there are just some types of people who are more likely to die. Those people remove themselves from the statistics pool once they die.
I'm not saying "THERE IS NO KILLING ZONE".. I'm saying "There is no evidence in that book which even begins to suggest there is one".
My gut instinct is that the longer you fly, the safer you are. It seems fairly intuitive to believe that, and your suggestion "i need to fly 300 hours before I'm safe" might not be wrong. But the thing you'd be very brave to assume is "I'm safe to take family and friends when I'm at 75 hours, but then once I get to about 120 hours, I need to stop flying them for a while as I'm less safe".
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Stats can be a real mind@#&? and it's a long time since I was a studied it but I'm pretty certain that this can't be right
All the boxes other than 57 and 100 are in the 'empty and will be removed' category with 0% chance of being winners. Box 57 and 100 (or more generically the box you chose originally and the final alternative) will have carried 50% probability from the start.
Any learned fellows able to comment on the logic?
Imagine that there are 100 boxes rather than 3. Your first guess is that the prize is in box 100. If the host now opens all the boxes except box 100 and box 57, the chance is now 99% that the prize is in box 57, and only 1% that it is in box 100.
Any learned fellows able to comment on the logic?
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Torque Tonight
When you first select. You DO (unquestionably) have twice as much chance of selecting an empty box.
When you get the chance to switch, nothing has changed about your original odds. It is still true that it is twice as likely that you had selected an empty box.
When you first select. You DO (unquestionably) have twice as much chance of selecting an empty box.
When you get the chance to switch, nothing has changed about your original odds. It is still true that it is twice as likely that you had selected an empty box.
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Stats can be a real mind@#&?
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Based entirely on the pilots i have flown with there is a degree of complacency that sets in after the first 100 hours running up to the first 600 hours. Beyond 600 hours it would seem they have usually had a fright or two, which is inevitable; to still be flying after 600 hours also means they probably take their flying more seriously.
I have flown with some pilots in the former category that i doubt would pass their ppl.
Were there a properly controlled study which adjusts for the factors raised earlier i would not be surprised if there were some truth in the premise.
I have flown with some pilots in the former category that i doubt would pass their ppl.
Were there a properly controlled study which adjusts for the factors raised earlier i would not be surprised if there were some truth in the premise.
