Respuesta :
Answer:
The mean is 4 mm and the standard deviation is 0.1414 mm
[tex]P(T>4.3)=0.017[/tex]
Step-by-step explanation:
Let's start defining the random variables.
[tex]T_{1}[/tex] : ''Thickness in mm of the first half''
[tex]T_{2}[/tex] : ''Thickness in mm of the second half''
The mean for this random variables is 2 (mm)
The standard deviation for this random variables is 0.1 mm
[tex]T_{1}[/tex] ~ N(2,0.1)
[tex]T_{2}[/tex] ~ N(2,0.1)
Now we calculate the variance of each random variable.
[tex](StandardDeviation)^{2}=Variance[/tex]
Therefore,
[tex](0.1mm)^{2}=0.01(mm^{2})[/tex]
The total thickness ''T'' is equal to
[tex]T=T_{1}+T_{2}[/tex]
Because of the independence between the halves and that T is the sum between two normally distributed random variables,
T ~ N [μ1 + μ2, [tex]\sqrt{Var(T1)+Var(T2)}[/tex]]
Where μ is the mean of the random variable
Where the mean for T is the sum of the means between [tex]T_{1}[/tex] and [tex]T_{2}[/tex] and the variance of T is the sum between the variances of [tex]T_{1}[/tex] and [tex]T_{2}[/tex]
μ1 + μ2 = 2 + 2 = 4
Var(T1) + Var(T2) = 0.01 + 0.01 = 0.02
The mean for T is 4 mm and the variance is [tex]0.02(mm^{2})[/tex]
The standard deviation is
[tex]\sqrt{0.02}=0.1414[/tex]
The standard deviation is 0.1414 mm
T ~ N (4,0.1414)
[tex]P(T>4.3)=1-P(T\leq 4.3)[/tex]
We subtract the mean and then we divide all by the standard deviation to obtained N(0,1)
Z ~ N(0,1) ⇒
[tex]1-P(T\leq 4.3)=1-P(\frac{T-4}{0.1414}\leq\frac{4.3-4}{0.1414})[/tex]
[tex]P(T>4.3)=1-P(Z\leq 2.1216)=[/tex] 1 - φ(2.1216)
Where φ(2.1216) is the value of the cumulative distribution of N(0,1) evaluated in 2.1216 (You can find this value on a table)
[tex]P(T>4.3)=1-0.9830=0.017[/tex]