Suppose the number of off springs a female eagle raises during its lifetime has a distribution with mean 18 and variance 4. In an area, 45 rescued and cured fe eagles are set free. If these eagles are assumed to be independent (no lack of male partners and food resources), the total number of off-springs produced by
Continuous Probability Distributions
Probability distributions are of two types, which are continuous probability distributions and discrete probability distributions. A continuous probability distribution contains an infinite number of values. For example, if time is infinite: you could count from 0 to a trillion seconds, billion seconds, so on indefinitely. A discrete probability distribution consists of only a countable set of possible values.
Normal Distribution
Suppose we had to design a bathroom weighing scale, how would we decide what should be the range of the weighing machine? Would we take the highest recorded human weight in history and use that as the upper limit for our weighing scale? This may not be a great idea as the sensitivity of the scale would get reduced if the range is too large. At the same time, if we keep the upper limit too low, it may not be usable for a large percentage of the population!
![Suppose the number of off springs a female eagle raises during its lifetime has a distribution with mean 18 and variance 4. In an area, 45 rescued and cured female
eagles are set free. If these eagles are assumed to be independent (no lack of male partners and food resources), the total number of off-springs produced by these
eagles can be assumed to have a Normal distribution with mean
and variance
pus
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