On Jan 22, 2013, at 13:45 , Prof Brian Ripley wrote:
> On 22/01/2013 11:49, Michael Haenlein wrote:
>> Dear all,
>>
>> I have a discrete distribution showing how age is distributed across a
>> population using a certain set of bands:
>>
>> Age <- matrix(c(74045062, 71978405, 122718362, 40489415
On 22/01/2013 11:49, Michael Haenlein wrote:
Dear all,
I have a discrete distribution showing how age is distributed across a
population using a certain set of bands:
Age <- matrix(c(74045062, 71978405, 122718362, 40489415), ncol=1,
dimnames=list(c("<18", "18-34", "35-64", "65+"),c()))
Age_dist
On Tue, Jan 22, 2013 at 11:49 AM, Michael Haenlein
wrote:
> I would like to find a continuous approximation of this discrete
> distribution in order to estimate the probability that a person is for
> example 16 years old.
Given that people age continuously (and continually...), you sound
like y
Dear all,
I have a discrete distribution showing how age is distributed across a
population using a certain set of bands:
Age <- matrix(c(74045062, 71978405, 122718362, 40489415), ncol=1,
dimnames=list(c("<18", "18-34", "35-64", "65+"),c()))
Age_dist <- Age/sum(Age)
For example I know that 23.94
4 matches
Mail list logo