A recent study of the lifetimes of cell phones found the average is 24.3 months. The standard deviation is 2.6 months. If a company provides its 33 employees with a cell phone, find the probability that the mean lifetime of these phones will be less than 23.8 months. Assume cell phone life is a normally distributed variable, the sample is taken from a large population and the correction factor can be ignored. Round the final answer to at least four decimal places and intermediate -value calculations to two decimal places.

Answer :

Answer:

[tex]P(\bar X<67.2)=P(\frac{X-\mu}{\sigma_{\bar X}}<\frac{23.8-\mu}{\sigma})=P(Z<\frac{23.8-24.3}{0.4526})=P(z<-1.11)[/tex]

And we can find this probability using the normal standard distribution or excel and we got:

[tex]P(z<-1.105)=0.1335[/tex]

Step-by-step explanation:

Let X the random variable that represent the lifetimes of cell phones, and for this case we know the distribution for X is given by:

[tex]X \sim N(24.3,2.6)[/tex]  

Where [tex]\mu=24.3[/tex] and [tex]\sigma=2.6[/tex]

We select a sample size of n = 33 emplloyees and we are interested on this probability

[tex]P(\bar X<23.8)[/tex]

And the best way to solve this problem is using the normal standard distribution and the z score given by:

[tex]z=\frac{x-\mu}{\frac{\sigma}{\sqrt{n}}}[/tex]

The standard deviation would be:

[tex]\sigma_{\bar X} = \frac{2.6}{\sqrt{33}}= 0.4526[/tex]

If we apply this formula to our probability we got this:

[tex]P(\bar X<67.2)=P(\frac{X-\mu}{\sigma_{\bar X}}<\frac{23.8-\mu}{\sigma})=P(Z<\frac{23.8-24.3}{0.4526})=P(z<-1.11)[/tex]

And we can find this probability using the normal standard distribution or excel and we got:

[tex]P(z<-1.105)=0.1335[/tex]

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