Answer:
36.58% probability that one of the devices fail
Step-by-step explanation:
For each device, there are only two possible outcomes. Either it fails, or it does not fail. The probability of a device failling is independent of other devices. So we use the binomial probability distribution to solve this question.
Binomial probability distribution
The binomial probability is the probability of exactly x successes on n repeated trials, and X can only have two outcomes.

In which
is the number of different combinations of x objects from a set of n elements, given by the following formula.

And p is the probability of X happening.
A total of 15 devices will be used.
This means that 
Assume that each device has a probability of 0.05 of failure during the course of the monitoring period.
This means that 
What is the probability that one of the devices fail?
This is 


36.58% probability that one of the devices fail
SOLUTION
We have been given the equation of the decay as

So we are looking for the time
Plugging the values into the equation, we have

Taking Ln of both sides, we have

Hence the answer is 4308 to the nearest year
Answer:
Domain is all values of X or (-∞,∞)
Range is all the possible values of Y. Since it goes up to 3, and then it goes down, it's all values less than or equal to y, or (-∞,3] or y ≤ 3 (depending on how you need to enter the response.
Step-by-step explanation:
Answer:
Q and S do not equal 0.
Step 1: Factor both the numerator and the denominator. ...
Step 2: Write as one fraction. ...
Step 3: Simplify the rational expression. ...
Step 4: Multiply any remaining factors in the numerator and/or denominator. ...
Step-by-step explanation:
~Riley~
Have a Good day!
Answer:
The probability that a randomly chosen Ford truck runs out of gas before it has gone 325 miles is 0.0062.
Step-by-step explanation:
Let <em>X</em> = the number of miles Ford trucks can go on one tank of gas.
The random variable <em>X</em> is normally distributed with mean, <em>μ</em> = 350 miles and standard deviation, <em>σ</em> = 10 miles.
If the Ford truck runs out of gas before it has gone 325 miles it implies that the truck has traveled less than 325 miles.
Compute the value of P (X < 325) as follows:

Thus, the probability that a randomly chosen Ford truck runs out of gas before it has gone 325 miles is 0.0062.