0.13 to 2 d.p.
The answer would depend on the demographics of the population: a probability of 0.2 it too high unless the population is from a retirement area.
sample
15 19
If the events can be considered independent then the probability is (0.7)4 = 0.24 approx.
Using the Poisson approximation, the probability is 0.0418
The answer depends on the demography of the population from which the person is randomly selected.The answer depends on the demography of the population from which the person is randomly selected.The answer depends on the demography of the population from which the person is randomly selected.The answer depends on the demography of the population from which the person is randomly selected.
Non probability sampling is where the samples are not selected randomly.
The answer would depend on the demographics of the population: a probability of 0.2 it too high unless the population is from a retirement area.
The probability that both will be hopelessly romantic is .0081 .009^2 = .0081
If I understand your question, yes, the proportion of people in a population ill with a certain disease at a given time is the same as the probablility that a randomly selected person in that population will have the disease at that time.
sample
In probability sampling,every item in the population has a known chance of being selected as a member.In non-probability sampling, the probability that any item in the population will be selected for a sample cannot be determined.
10/12
The answer will depend on what the disease is.
15 19
85/500 = 17%
If the events can be considered independent then the probability is (0.7)4 = 0.24 approx.