What’s the point of keeping seven-digit precision? Especially in spite of the fact that your calculation includes a disproportionately rough guess of “an average age of ten”, another fact that the life expectancy estimates from different sources can differ up to 10% from each other and the problematic assumption that if you save a ten-year old child, his or her expected survival time is equal to the country’s life expectancy minus ten? (The data of life expectancy are usually given at birth. Poor countries have usually relatively high child mortality; if you survive until the age of ten, your life expectancy is much higher than the listed figure.)
your recreation time would need to be ~931 times as valuable as an equivalent amount of time in a third world person’s life
I refrained from rounding until the end so that if people were following my calculations starting from partway through they would arrive at the same answers. It wasn’t really necessary, and now that you mention it it does raise questions about significant digits, so I’ll round midway figures for display in the future.
Good point on the life expectancy being given for people currently born. I’ll edit the post to use life expectancy figures from ten years ago.
if people were following my calculations starting from partway through they would arrive at the same answers
If this is motivated by desire for trustworthiness, linking to the source of the life expectancy figures should have higher priority. (Also, how did you calculate the average? Weighed by overall population of those countries, population under ten, number of AMF clients, simply averaging the four numbers, … ?)
I’ll edit the post to use life expectancy figures from ten years ago.
If you used the ten years old data, you would most probably obtain lower expected age at death for today’s ten-years olds* than for today’s newborns. But it should be higher. The problem is not that the life expectancy changes during the time. The problem is that the life expectancy at birth is average of life times of all people born, while the life expectancy at age of ten is average of life times* of all people that survived until this age. The latter is higher than the former, since all children who died before their tenth birthday (and who lower the former average) are excluded from the statistics. In e.g. Zambia, about 11% of children die before age of five, so you can imagine how this influences the discussed difference. (I was unable to quickly find data for this to illustrate the difference explicitly.)
* Note that life expectancy at age x usually means the expected remaining time of life, not the expected age of death (which obviously is obtained from the former by adding x).
I simply averaged the four numbers on those countries. I’ll edit the post to have a weighted average by number of nets distributed.
I don’t know how to account for disproportionate early deaths in my calculations, since I don’t have data on the typical lifespan of, for instance, a Zambian who survives childhood.
Just to be clear: I am not objecting that your numbers are imprecise. Your argument doesn’t require precision. I have objected to incompatible levels of precision involved in the presentation: rough guesses and systematic errors of order 10% or more (some of them unavoidable) on the one hand and five-decimal figures on the other hand.
What’s the point of keeping seven-digit precision?
Note that basing precision on powers of ten is not particularly well-motivated. It arguably makes sense in the sciences where SI is used, but not in general.
Writing 38 instead of 38.81755 saves 6 characters, if nothing else. Keeping unnecessarily many decimals also creates impression of a high precision figure which was misleading here. I am not sure what SI and sciences have to do with that; we use the decimal system for writing numbers, our language is adopted to the decimal system (which is why it may be even preferable to say 40 instead of 38 in the present context—it’s shorter when said aloud) and SI is decimal because of these facts, not the other way around.
Sorry, by using the word ‘precision’ I thought you were invoking the concept of ‘significant figures’, which is used to correctly represent the amount of information in your answer, based on the maximum precision of your instruments. I would argue that in general, binary significant figures are better for that purpose than decimal.
The reason SI is relevant to that, is that the measurements you take tend to be on instruments that are precise to a particular decimal digit. Compare to US units, which are often divided successively in half and thus are much more naturally amenable to binary.
Binary significant figures are better for measuring amount of information, no doubt. But since the numbers are written in the decimal base it is easier to work with decimal significant figures; the ‘instruments’ for measuring life expectancy are statistical surveys which are usually conducted in base 10 (although the units are years, which aren’t particularly SI).
What’s the point of keeping seven-digit precision? Especially in spite of the fact that your calculation includes a disproportionately rough guess of “an average age of ten”, another fact that the life expectancy estimates from different sources can differ up to 10% from each other and the problematic assumption that if you save a ten-year old child, his or her expected survival time is equal to the country’s life expectancy minus ten? (The data of life expectancy are usually given at birth. Poor countries have usually relatively high child mortality; if you survive until the age of ten, your life expectancy is much higher than the listed figure.)
It is even more valuable for me.
I refrained from rounding until the end so that if people were following my calculations starting from partway through they would arrive at the same answers. It wasn’t really necessary, and now that you mention it it does raise questions about significant digits, so I’ll round midway figures for display in the future.
Good point on the life expectancy being given for people currently born. I’ll edit the post to use life expectancy figures from ten years ago.
If this is motivated by desire for trustworthiness, linking to the source of the life expectancy figures should have higher priority. (Also, how did you calculate the average? Weighed by overall population of those countries, population under ten, number of AMF clients, simply averaging the four numbers, … ?)
If you used the ten years old data, you would most probably obtain lower expected age at death for today’s ten-years olds* than for today’s newborns. But it should be higher. The problem is not that the life expectancy changes during the time. The problem is that the life expectancy at birth is average of life times of all people born, while the life expectancy at age of ten is average of life times* of all people that survived until this age. The latter is higher than the former, since all children who died before their tenth birthday (and who lower the former average) are excluded from the statistics. In e.g. Zambia, about 11% of children die before age of five, so you can imagine how this influences the discussed difference. (I was unable to quickly find data for this to illustrate the difference explicitly.)
* Note that life expectancy at age x usually means the expected remaining time of life, not the expected age of death (which obviously is obtained from the former by adding x).
(Edited.)
I simply averaged the four numbers on those countries. I’ll edit the post to have a weighted average by number of nets distributed. I don’t know how to account for disproportionate early deaths in my calculations, since I don’t have data on the typical lifespan of, for instance, a Zambian who survives childhood.
Just to be clear: I am not objecting that your numbers are imprecise. Your argument doesn’t require precision. I have objected to incompatible levels of precision involved in the presentation: rough guesses and systematic errors of order 10% or more (some of them unavoidable) on the one hand and five-decimal figures on the other hand.
Note that basing precision on powers of ten is not particularly well-motivated. It arguably makes sense in the sciences where SI is used, but not in general.
Writing 38 instead of 38.81755 saves 6 characters, if nothing else. Keeping unnecessarily many decimals also creates impression of a high precision figure which was misleading here. I am not sure what SI and sciences have to do with that; we use the decimal system for writing numbers, our language is adopted to the decimal system (which is why it may be even preferable to say 40 instead of 38 in the present context—it’s shorter when said aloud) and SI is decimal because of these facts, not the other way around.
Sorry, by using the word ‘precision’ I thought you were invoking the concept of ‘significant figures’, which is used to correctly represent the amount of information in your answer, based on the maximum precision of your instruments. I would argue that in general, binary significant figures are better for that purpose than decimal.
The reason SI is relevant to that, is that the measurements you take tend to be on instruments that are precise to a particular decimal digit. Compare to US units, which are often divided successively in half and thus are much more naturally amenable to binary.
Binary significant figures are better for measuring amount of information, no doubt. But since the numbers are written in the decimal base it is easier to work with decimal significant figures; the ‘instruments’ for measuring life expectancy are statistical surveys which are usually conducted in base 10 (although the units are years, which aren’t particularly SI).