Statement Q1. The lifetime, in years, of a certain type of fuel cell is a randomvariable with probability density function k X>0 f(x) = { (x+ 3)* x<0 Using i. Detemine the value kso that f(x) becomes a pdf. ii. Using cumulative distribution function (CDF) method finds the probability that a fuel cell lasts more than 5 years? Find the coefficient of variation of x+3 РX>20 | X<40). iii. iv.
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!
![Statement
Q1. The lifetime, in years, of a certain type of fuel cell is a randomvariable with probability
density function
k
X>0
f(x) = { (x+ 3)*
x<0
Using
i.
Detemine the value kso that f(x) becomes a pdf.
ii.
Using cumulative distribution function (CDF) method finds the probability
that a fuel cell lasts more than 5 years?
iii.
Find the coefficient of variation of x+3
iv.
РX>20 |X<40).](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Ffeebae99-56af-4762-a252-d4d59839fd53%2F6d8fd95f-a719-4ee4-be37-b550b9bd9f4d%2Fhcu9yz_processed.png&w=3840&q=75)
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