The Poisson distribution defines the probability of k discrete and independent events occurring in a given time interval.
If λ = the average number of event occurring within the given interval, then
For the given problem,
λ = 6.5, average number of tickets per day.
k = 6, the required number of tickets per day
The Poisson distribution is
The distribution is graphed as shown below.
Answer:
The mean is λ = 6.5 tickets per day, and it represents the expected number of tickets written per day.
The required value of k = 6 is less than the expected value, therefore the department's revenue target is met on an average basis.
Answer:
a) Mean Time to failure (MTTF) = (10^7) hours
b) Availability of the system = 1
c) Mean Time to failure for 1000 processors = 10^4 hours.
Step-by-step explanation:
a) Failures in time (FIT) is traditionally reported as failure Per billion hours Of Operation.
1 billion = (10^9)
FIT = 100/(10^9) = 10^-7
MTTF = 1/FIT = 1/(10^-7) = (10^7) hours
b) Availability of the system = MTTF/(MTTF + MTTR)
MTTR = mean time to repair = 24hours
Availability of the system = (10^7)/((10^7) + 24) = 0.9999 = 1
c) FIT = 1000 (processors) × 100 (FIT per processor) = (10^5) per billion hours of operations = (10^5)/(10^9) = 10^-4
MTTF = 1/FIT = 1/(10^-4) = (10^4) hours
QED!!
Answer:
x/6 - 1
Step-by-step explanation:
x divide 6 subtract 1
Answer:
Either -4n or 0n but most likely -4n
Answer:
See below
Step-by-step explanation:
<u>Parent function:</u>
<u>Transformed function:</u>
- y = 4(3)⁻²ˣ⁺⁸ + 6, (note. I see this as 8, sorry if different but it doesn't make any change to transformation method)
<u>Transformations to be applied:</u>
- f(x) → f(-x) reflection over y-axis
- f(-x) → f(-2x) stretch horizontally by a factor of 2
- f(-2x) → f(-2x + 8) translate 8 units right
- f(-2x + 8) → 4f(-2x + 8) stretch vertically by a factor of 4
- 4f(-2x + 8) → 4f(-2x + 8) + 6 translate 6 units up