A manufacturing company has developed a machine for cleaning carpet that is fuel-efficient because it delivers carpet cleaner so rapidly. Of interest is a random variable Y, the amount in gallons per minute delivered. It is known that the density function is given to the right. Complete parts (a) and (b) below. 2sys6, 4' f(y) = 0, elsewhere (a) Sketch the density function. Choose the correct graph below. A. В. D. Af(y) 1.2- Af(y) 1.2- Af(y) 1.2- Af(y) 12- 0.9- 0.6- 0.9- 0.9- 9- 0.6- 0.6- 6- 0.3- 0.3 0.3 3-
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!
Probability density also called as distribution function which represents the density of a continuous random variable lying between some values.
The density function is defined for continuous value and the mass function is defined for discrete values.
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