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Answer:
Step-by-step explanation:
From the information given:
mean life span of a brand of automobile = 35,000
standard deviation of a brand of automobile = 2250 miles.
the z-score that corresponds to each life span are as follows.
the standard z- score formula is:
[tex]z = \dfrac{x - \mu}{\sigma}[/tex]
For x = 34000
[tex]z = \dfrac{34000 - 35000}{2250}[/tex]
[tex]z = \dfrac{-1000}{2250}[/tex]
z = −0.4444
For x = 37000
[tex]z = \dfrac{37000 - 35000}{2250}[/tex]
[tex]z = \dfrac{2000}{2250}[/tex]
z = 0.8889
For x = 3000
[tex]z = \dfrac{30000 - 35000}{2250}[/tex]
[tex]z = \dfrac{-5000}{2250}[/tex]
z = -2.222
From the above z- score that corresponds to their life span; it is glaring that the tire with the life span 30,000 miles has an unusually short life span.
For x = 30,500
[tex]z = \dfrac{30500 - 35000}{2250}[/tex]
[tex]z = \dfrac{-4500}{2250}[/tex]
z = -2
P(z) = P(-2)
Using excel function (=NORMDIST -2)
P(z) = 0.022750132
P(z) = 2.28th percentile
For x = 37250
[tex]z = \dfrac{37250 - 35000}{2250}[/tex]
[tex]z = \dfrac{2250}{2250}[/tex]
z = 1
Using excel function (=NORMDIST 1)
P(z) = 0.841344746
P(z) = 84.14th percentile
For x = 35000
[tex]z = \dfrac{35000- 35000}{2250}[/tex]
[tex]z = \dfrac{0}{2250}[/tex]
z = 0
Using excel function (=NORMDIST 0)
P(z) = 0.5
P(z) = 50th percentile
a. The z score of each life span should be -0.4444, 0.889, and 2.2222.
b. The percentile of each life span should be 0.0228, 0.8413 and 0.5000.
Given that,
- mean life span of 35,000 miles, with a standard deviation of 2250 miles.
The calculation is as follows:
(a)
The z score should be
[tex]Z1 = \frac{34000-35000}{2250} = -0.4444\\\\Z2 = \frac{37000-35000}{2250} = 0.8889\\\\Z3 = \frac{30000-35000}{2250} = -2.2222\\\\[/tex]
The tire with life span of 30000 miles would be considered unusual
(b)
The percentile should be
[tex]Z1 = \frac{30500-35000}{2250} = -2[/tex]
p(Z1 < -2) = NORMSDIST(-2) = 0.0228
[tex]Z2 = \frac{37250-35000}{2250} = 1[/tex]
p(Z2 < 1) = NORMSDIST(1) = 0.8413
[tex]Z3 = \frac{35000-35000}{2250} = 0[/tex]
p(Z3 < 0) = NORMSDIST(0) = 0.5000
Find out more information about standard deviation here:
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