Answer:
Step-by-step explanation:
The diagram for the question is attached below
perimeter of the triangle is 28 feet
area of a square is 144 feet
Area of the square is side^2
take square root on both sides
side = 12
side of the square = 12
side is the diameter of the semicircle
Diameter = 12 , so radius = 12 divide 2 = 6
circumference of semicircle = 
one side of the rectangle is calculated in the perimeter of triangle and other side is calculated using circumference
perimeter of other two side = 2(12)= 24
Total perimeter = 
Answer:
Step-by-step explanation:
The probability that Rachel will win the game is: 1/12
Step-by-step explanation:
The number cubes has six sides numbered between 1 to 6. the chances of each number are equally likely
Let S be the sample space
The sample space has 6*6 = 36 outcomes.
Now, Let A be the event that the sum of numbers on both number cubes is 10
A = {(4,6),(5,5), (6,4)
n(A) = 3
The probability that Rachel will win the game is: 1/12
Keywords: Probability, Sample
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As the exterior angles always add up to 360, you can find the number of sides by dividing 360 by the measure of your exterior angle, 30. This gives you 360/30=12, meaning your polygon has 12 sides.
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.
