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Maru [420]
3 years ago
12

a rabbit falls into a dry well 30 meters deep. since being at the bottom of a well she tries to go up 3 meters but falls down 2

meters. how many days does it take her to get out of the well?
Mathematics
1 answer:
myrzilka [38]3 years ago
3 0

I believe the correct answer is the 27th day, since it goes up three each day and down 2 each day.  Kinda like this

Day 1: Up 3 - 2 = 1

Day 2: Your starting point is now 1.  1 + 3 - 2 = 2

And then it would keep on going up by ones until you reached day 27.  Then it will be Day 27: 27 + 3 - 2.  However on that day the rabbit would've already reached the top of the well and would not have slid down the two meters.  Hope this long kinda confusing explanation is correct and helpful.

-TTL

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a) P(X>30000)=1-( 1- e^{-\frac{30000}{30000}})=e^{-1}=0.368

b) P(X>30000|X>15000)=P(X>15000)=1-( 1- e^{-\frac{15000}{30000}})=e^{-0.5}=0.607

Step-by-step explanation:

Previous concepts

The exponential distribution is "the probability distribution of the time between events in a Poisson process (a process in which events occur continuously and independently at a constant average rate). It is a particular case of the gamma distribution". The probability density function is given by:

P(X=x)=\lambda e^{-\lambda x}, x>0

And 0 for other case. Let X the random variable that represent "life lengths of automobile tires of a certain brand" and we know that the distribution is given by:

X \sim Exp(\lambda=\frac{1}{30000})

The cumulative distribution function is given by:

F(X) = 1- e^{-\frac{x}{\mu}}

Part a

We want to find this probability:

P(X>30000) and for this case we can use the cumulative distribution function to find it like this:

P(X>30000)=1-( 1- e^{-\frac{30000}{30000}})=e^{-1}=0.368

Part b

For this case w want to find this probability

P(X>30000|X>15000)

We have an important property on the exponential distribution called "Memoryless" property and says this:

P(X>a+t| X>t)=P(X>a)  

On this case if we use this property we have this:P(X>30000|X>15000)=P(X>15000+15000|X>15000)=P(X>15000)

We can use the definition of the density function and find this probability:

P(X>15000)=1-( 1- e^{-\frac{15000}{30000}})=e^{-0.5}=0.607

7 0
3 years ago
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