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Barrett and Marshall Model for conception: A biologically reasonable model for the probability of conception in a particular menstrual cycle, which supposes that the batches of sperm introduced on different days behave without any dependency. The model is
where the Xik are 0,1 variables corresponding to whether there was the intercourse or not on a particular day relative to the estimated day of the ovulation (which is day 0). The parameter pi is interpreted as the probability that the conception would happen following intercourse on the day i only.
The problem that the studies are not uniformly probable to be published in the scientific journals. There is evidence that the statistical significance is a main determining factor
Quota sample is the sample in which the units are not selected at the random, but in terms of a particular number of units in each of a number of categories; for instance, 10 men
I have a problem I am trying to solve. An oil company thinks that there is a 60% chance that there is oil in the land they own. Before drilling they run a soil test. When there is
Geo statistics: The body of methods useful for understanding and modelling spatial variability in a course of interest. Central to these techniques is the idea that measurements t
This is given by common network e.g. Phone Company. The public networks are those networks, which are given by common carriers. It can be a telephone company or an other organizati
The biggest and smallest variate values among the sample of observations. Significant in various regions, for instance flood levels of the river, speed of wind and snowfall.
Probability judgements : Human beings often require assessing the probability which some event will occur and accuracy of these probability judgements often determines success of o
Genetic algorithms: The optimization events motivated by the biological analogies. The prime idea is to try to mimic the 'survival of the fittest' rule of the genetic mutation in
Window estimates is a term which occurs in the context of the both frequency domain and time domain estimation for the time series. In the previous it generally applies to weights
1) Let N1(t) and N2(t) be independent Poisson processes with rates, ?1 and ?2, respectively. Let N (t) = N1(t) + N2(t). a) What is the distribution of the time till the next epoch
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