R Dataset / Package HistData / HalleyLifeTable
On this Rdata statistics page, you will find information about the HalleyLifeTable data set which pertains to Halley's Life Table. The HalleyLifeTable data set is found in the HistData R package. You can load the HalleyLifeTable data set in R by issuing the following command at the console data("HalleyLifeTable"). This will load the data into a variable called HalleyLifeTable. If R says the HalleyLifeTable data set is not found, you can try installing the package by issuing this command install.packages("HistData") and then attempt to reload the data with the library() command. If you need to download R, you can go to the R project website. You can download a CSV (comma separated values) version of the HalleyLifeTable R data set. The size of this file is about 2,262 bytes.
Halley's Life Table
Description
In 1693 the famous English astronomer Edmond Halley studied the birth and death records of the city of Breslau, which had been transmitted to the Royal Society by Caspar Neumann. He produced a life table showing the number of people surviving to any age from a cohort born the same year. He also used his table to compute the price of life annuities.
Usage
data("HalleyLifeTable")
Format
A data frame with 84 observations on the following 4 variables.
age

a numeric vector
deaths

number of deaths, D_k, among people of age k, a numeric vector
number

size of the population, P_k surviving until this age, a numeric vector
ratio

the ratio P_{k+1}/P_k, the conditional probability of surviving until age k + 1 given that one had already reached age k, a numeric vector
Details
Halley's table contained only age
and number
. For people aged over 84 years, Halley just noted that their total number was 107. This value is not included in the data set.
The data from Breslau had a mean of 1,238 births per year: this is the value that Halley took for the size, P_0 of the population cohort at age 0. From the data, he could compute the annual mean D_k of the number of deaths among people aged k for all k >= 0. From this, he calculated the number P_{k+1} surviving one more year,
P_{k+1} = P_k  D_k
This method had the great advantage of not requiring a general census but only knowledge of the number of births and deaths and of the age at which people died during a few years.
Source
N. Bacaer (2011), "Halley's life table (1693)", Ch 2, pp 510. In A Short History of Mathematical Population Dynamics, SpringerVerlag London, DOI 10.1007/9780857291158_2. Data taken from Table 1.
References
Halley, E. (1693). An estimate of the degrees of the mortality of mankind, drawn from curious tables of the births and funerals at the city of Breslaw; with an attempt to ascertain the price of annuities upon lives. Philosophical Transactions of the Royal Society, London, 17, 596610.
The text of Halley's paper was found at http://www.pierremarteau.com/editions/1693mortality.html
See Also
Arbuthnot
Examples
data(HalleyLifeTable) # what was the estimated population of Breslau? sum(HalleyLifeTable$number)# plot survival vs. age plot(number ~ age, data=HalleyLifeTable, type="h", ylab="Number surviving")# population pyramid is transpose of this plot(age ~ number, data=HalleyLifeTable, type="l", xlab="Number surviving") with(HalleyLifeTable, segments(0, age, number, age, lwd=2))# conditional probability of survival, one more year plot(ratio ~ age, data=HalleyLifeTable, ylab="Probability survive one more year")
Dataset imported from https://www.rproject.org.