Answer:
Given - A rectangle of length 18 feet and wide 14 feet
To find - Area
Solution -
Area of rectangle = Length * Breadth
=
![18 \times 14](https://tex.z-dn.net/?f=18%20%5Ctimes%2014)
square feet
Part a)
It was given that 3% of patients gained weight as a side effect.
This means
![p = 0.03](https://tex.z-dn.net/?f=p%20%3D%200.03)
![q = 1 - 0.03 = 0.97](https://tex.z-dn.net/?f=q%20%3D%201%20-%200.03%20%3D%200.97)
The mean is
![\mu = np](https://tex.z-dn.net/?f=%20%5Cmu%20%20%3D%20np)
![\mu = 643 \times 0.03 = 19.29](https://tex.z-dn.net/?f=%20%5Cmu%20%3D%20643%20%5Ctimes%200.03%20%3D%2019.29)
The standard deviation is
![\sigma = \sqrt{npq}](https://tex.z-dn.net/?f=%20%5Csigma%20%3D%20%20%5Csqrt%7Bnpq%7D%20)
![\sigma = \sqrt{643 \times 0.03 \times 0.97}](https://tex.z-dn.net/?f=%20%5Csigma%20%3D%20%20%5Csqrt%7B643%20%5Ctimes%200.03%20%5Ctimes%200.97%7D%20)
![\sigma =4.33](https://tex.z-dn.net/?f=%20%5Csigma%20%3D4.33)
We want to find the probability that exactly 24 patients will gain weight as side effect.
P(X=24)
We apply the Continuity Correction Factor(CCF)
P(24-0.5<X<24+0.5)=P(23.5<X<24.5)
We convert to z-scores.
![P(23.5 \: < \: X \: < \: 24.5) = P( \frac{23.5 - 19.29}{4.33} \: < \: z \: < \: \frac{24.5 - 19.29}{4.33} ) \\ = P( 0.97\: < \: z \: < \: 1.20) \\ = 0.051](https://tex.z-dn.net/?f=P%2823.5%20%5C%3A%20%3C%20%5C%3A%20X%20%5C%3A%20%3C%20%5C%3A%2024.5%29%20%3D%20P%28%20%5Cfrac%7B23.5%20-%2019.29%7D%7B4.33%7D%20%5C%3A%20%3C%20%5C%3A%20z%20%5C%3A%20%3C%20%5C%3A%20%20%5Cfrac%7B24.5%20-%2019.29%7D%7B4.33%7D%20%29%20%5C%5C%20%20%3D%20P%28%200.97%5C%3A%20%3C%20%5C%3A%20z%20%5C%3A%20%3C%20%5C%3A%20%201.20%29%20%5C%5C%20%20%3D%200.051)
Part b) We want to find the probability that 24 or fewer patients will gain weight as a side effect.
P(X≤24)
We apply the continuity correction factor to get;
P(X<24+0.5)=P(X<24.5)
We convert to z-scores to get:
![P(X \: < \: 24.5) = P(z \: < \: \frac{24.5 - 19.29}{4.33} ) \\ = P(z \: < \: 1.20) \\ = 0.8849](https://tex.z-dn.net/?f=P%28X%20%5C%3A%20%3C%20%5C%3A%2024.5%29%20%3D%20P%28z%20%5C%3A%20%3C%20%5C%3A%20%20%5Cfrac%7B24.5%20-%2019.29%7D%7B4.33%7D%20%29%20%20%5C%5C%20%3D%20%20%20P%28z%20%5C%3A%20%3C%20%5C%3A%201.20%29%20%20%5C%5C%20%20%3D%200.8849)
Part c)
We want to find the probability that
11 or more patients will gain weight as a side effect.
P(X≥11)
Apply correction factor to get:
P(X>11-0.5)=P(X>10.5)
We convert to z-scores:
![P(X \: > \: 10.5) = P(z \: > \: \frac{10.5 - 19.29}{4.33} ) \\ = P(z \: > \: - 2.03)](https://tex.z-dn.net/?f=P%28X%20%5C%3A%20%3E%20%5C%3A%2010.5%29%20%3D%20P%28z%20%5C%3A%20%3E%20%5C%3A%20%20%5Cfrac%7B10.5%20-%2019.29%7D%7B4.33%7D%20%29%20%20%5C%5C%20%3D%20P%28z%20%5C%3A%20%3E%20%5C%3A%20%20-%202.03%29)
![= 0.9788](https://tex.z-dn.net/?f=%20%3D%200.9788)
Part d)
We want to find the probability that:
between 24 and 28, inclusive, will gain weight as a side effect.
P(24≤X≤28)=
P(23.5≤X≤28.5)
Convert to z-scores:
![P(23.5 \: < \: X \: < \: 28.5) = P( \frac{23.5 - 19.29}{4.33} \: < \: z \: < \: \frac{28.5 - 19.29}{4.33} ) \\ = P( 0.97\: < \: z \: < \: 2.13) \\ = 0.1494](https://tex.z-dn.net/?f=P%2823.5%20%20%5C%3A%20%20%3C%20%20%5C%3A%20X%20%5C%3A%20%20%3C%20%20%5C%3A%2028.5%29%20%3D%20P%28%20%5Cfrac%7B23.5%20-%2019.29%7D%7B4.33%7D%20%20%20%5C%3A%20%20%3C%20%20%5C%3A%20z%20%5C%3A%20%20%3C%20%20%5C%3A%20%20%5Cfrac%7B28.5%20-%2019.29%7D%7B4.33%7D%20%29%20%5C%5C%20%20%3D%20P%28%200.97%5C%3A%20%20%3C%20%20%5C%3A%20z%20%5C%3A%20%20%3C%20%20%5C%3A%202.13%29%20%5C%5C%20%20%3D%200.1494)
B is 12
c is 6 because you don't count the zero
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