Answer:
a) P(x=3)=0.089
b) P(x≥3)=0.938
c) 1.5 arrivals
Step-by-step explanation:
Let t be the time (in hours), then random variable X is the number of people arriving for treatment at an emergency room.
The variable X is modeled by a Poisson process with a rate parameter of λ=6.
The probability of exactly k arrivals in a particular hour can be written as:

a) The probability that exactly 3 arrivals occur during a particular hour is:

b) The probability that <em>at least</em> 3 people arrive during a particular hour is:
![P(x\geq3)=1-[P(x=0)+P(x=1)+P(x=2)]\\\\\\P(0)=6^{0} \cdot e^{-6}/0!=1*0.0025/1=0.002\\\\P(1)=6^{1} \cdot e^{-6}/1!=6*0.0025/1=0.015\\\\P(2)=6^{2} \cdot e^{-6}/2!=36*0.0025/2=0.045\\\\\\P(x\geq3)=1-[0.002+0.015+0.045]=1-0.062=0.938](https://tex.z-dn.net/?f=P%28x%5Cgeq3%29%3D1-%5BP%28x%3D0%29%2BP%28x%3D1%29%2BP%28x%3D2%29%5D%5C%5C%5C%5C%5C%5CP%280%29%3D6%5E%7B0%7D%20%5Ccdot%20e%5E%7B-6%7D%2F0%21%3D1%2A0.0025%2F1%3D0.002%5C%5C%5C%5CP%281%29%3D6%5E%7B1%7D%20%5Ccdot%20e%5E%7B-6%7D%2F1%21%3D6%2A0.0025%2F1%3D0.015%5C%5C%5C%5CP%282%29%3D6%5E%7B2%7D%20%5Ccdot%20e%5E%7B-6%7D%2F2%21%3D36%2A0.0025%2F2%3D0.045%5C%5C%5C%5C%5C%5CP%28x%5Cgeq3%29%3D1-%5B0.002%2B0.015%2B0.045%5D%3D1-0.062%3D0.938)
c) In this case, t=0.25, so we recalculate the parameter as:

The expected value for a Poisson distribution is equal to its parameter λ, so in this case we expect 1.5 arrivals in a period of 15 minutes.

Answer:
P ( 37 < x < 41) = P(-0.5 < Z < 1.5) = 0.6247
Step-by-step explanation:
We know mean u = 38 standard dev. s = 2
We want P ( 37 < x < 41)
so
P( (37 - 38) / 2 < Z) = P(-0.5 < Z)
P( Z < (41 - 38)/2 ) = P( Z < 1.5)
Find P(Z < -0.5) = 0.3085
Find P(Z > 1.5) = 0.0668
so P(-0.5 < Z < 1.5) = 1 - P(Z < -0.5) - P(Z > 1.5)
P(-0.5 < Z < 1.5) = 1 - 0.3085 - 0.0668
P(-0.5 < Z < 1.5) = 0.6247
P ( 37 < x < 41) = P(-0.5 < Z < 1.5) = 0.6247
Answer:
92
Step-by-step explanation:
angle a and b add up to 180 degrees
4x-20+2x+8=180
add like terms
6x+12=180
x=28
then substitute to get 92