For this case we have the following number:
45.972
By definition we have to:
hundredths place: place located two digits to the right of the decimal point.
We have then that for this case the number located in hundredths place is:
7
Answer:
there are 7 hundredths in 45.972
Answer:
pennies
Step-by-step explanation:
because they are thinner than notebooks and you will need more of them
Answer:
3 x^3 y^4 sqrt(5x)
Step-by-step explanation:
sqrt(45x^7y^8)
We know that sqrt(ab) = sqrt(a)sqrt(b)
sqrt(45)sqrt(x^7) sqrt(y^8)
sqrt(9*5) sqrt(x^2 *x^2 * x^2* x) sqrt(y^2 *y^2 *y^2 *y^2)
We know that sqrt(ab) = sqrt(a)sqrt(b)
sqrt(9)sqrt(5) sqrt(x^2)sqrt(x^2) sqrt(x^2) sqrt(x) sqrt(y^2)sqrt(y^2)sqrt(y^2)sqrt(y^2)
3 sqrt(5) x*x*x sqrt(x) y*y*y*y
3 x^3 y^4 sqrt(5)sqrt(x)
3 x^3 y^4 sqrt(5x)
Answer:
.20$
Step-by-step explanation:
4 1/2=4.5
4.5 divided by 22.50=.20
Answer:
a) 
b) 
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:

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:

The cumulative distribution function is given by:

Part a
We want to find this probability:
and for this case we can use the cumulative distribution function to find it like this:

Part b
For this case w want to find this probability

We have an important property on the exponential distribution called "Memoryless" property and says this:
On this case if we use this property we have this:
We can use the definition of the density function and find this probability:
