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enot [183]
3 years ago
14

Inverse of f(x)={(0,1),(1,4),(2,3)}

Mathematics
1 answer:
lilavasa [31]3 years ago
7 0

f^{-1}(x)=\{(1,0),(3,2),(4,1)\}

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If someone could please help me then that would be great.
postnew [5]

Answer: Infinite Solutions

Step-by-step explanation: Make the top x and y values times -2 to cancel all the variables and numbers out to get 0 = 0 so it would be Infinite Solutions.

And if you multiply by 2 you get the exact same equation.

If I am wrong let me know!

Hope this helps!  

6 0
3 years ago
Help me with this and my other questions
Vikentia [17]
Number 7 you divide 6.48 by 4
8 0
3 years ago
-sqr(4x+6)-15<br><br> Find the domain.
Maksim231197 [3]

Answer:

Step-by-step explanation:

6 0
2 years ago
Under average driving conditions, the life lengths of automobile tires of a certain brand are found to follow an exponential dis
wariber [46]

Answer:

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
Please help it’s urgent . Grade 11 homework
AlexFokin [52]

Answer:

(l) y=2x-2

(ll) y=4x+1

(lll) y=5x+13

(lV) y=-3x-6

(V) y=-5x-17

(Vl) y=(2/3)x-3

5 0
1 year ago
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