The final answer is:
a) P( Y < 42.5 ) = 0.8541
b) P( 39.5 < Y < 40.5 ) = 0.1670.
What is the normal distribution?
A continuous probability distribution for a real-valued random variable in statistics is known as a normal distribution or Gaussian distribution.
If x follows a normal distribution with mean μ and standard deviation σ then the distribution of
follows an approximately normal distribution with a mean
and standard deviation
let x be the height of blades of grass
x follows normal distribution with mean = μ = 4 and standard deviation = σ = 0.75.
Y = x1 + x2 +...........+x10
![Y = \sum_{i =1}^{10}x_{i}](https://tex.z-dn.net/?f=Y%20%3D%20%5Csum_%7Bi%20%3D1%7D%5E%7B10%7Dx_%7Bi%7D)
Distribution of Y is normal with,
Mean =
and standard deviation ![= \sigma _{y}=\sqrt{10}*0.75 = 2.3717](https://tex.z-dn.net/?f=%3D%20%5Csigma%20_%7By%7D%3D%5Csqrt%7B10%7D%2A0.75%20%3D%202.3717)
a)
P( Y < 42.5 )
Using normal distribution formmula,
![f(x)= {\frac{1}{\sigma\sqrt{2\pi}}}e^{- {\frac {1}{2}} (\frac {x-\mu}{\sigma})^2}](https://tex.z-dn.net/?f=f%28x%29%3D%20%7B%5Cfrac%7B1%7D%7B%5Csigma%5Csqrt%7B2%5Cpi%7D%7D%7De%5E%7B-%20%7B%5Cfrac%20%7B1%7D%7B2%7D%7D%20%28%5Cfrac%20%7Bx-%5Cmu%7D%7B%5Csigma%7D%29%5E2%7D)
=NORMDIST( x, mean, SD , 1 )
=NORMDIST(42.5, 40, 2.3717, 1 )
=0.8541
P( Y < 42.5 ) = 0.8541
b)
P( 39.5 < Y < 40.5 ) = P( Y < 40.5 ) - P( Y < 39.5 )
Using normal distribution formmula,
![f(x)= {\frac{1}{\sigma\sqrt{2\pi}}}e^{- {\frac {1}{2}} (\frac {x-\mu}{\sigma})^2}](https://tex.z-dn.net/?f=f%28x%29%3D%20%7B%5Cfrac%7B1%7D%7B%5Csigma%5Csqrt%7B2%5Cpi%7D%7D%7De%5E%7B-%20%7B%5Cfrac%20%7B1%7D%7B2%7D%7D%20%28%5Cfrac%20%7Bx-%5Cmu%7D%7B%5Csigma%7D%29%5E2%7D)
P( Y < 40.5 ) =NORMDIST(40.5, 40, 2.3717, 1 ) = 0.5835
P( Y < 39.5 ) = NORMDIST(39.5, 40, 2.3717, 1 ) = 0.4165
P( 39.5 < Y < 40.5 ) = 0.5835 - 0.4165 = 0.1670
P( 39.5 < Y < 40.5 ) = 0.1670
Hence, the final answer is:
a) P( Y < 42.5 ) = 0.8541
b) P( 39.5 < Y < 40.5 ) = 0.1670.
To learn more about the normal distribution visit,
brainly.com/question/4079902
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